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Moldovan, C., Wamser, F., Hoßfeld, T.: Energy-Efficient Adaptation Logic for HTTP Streaming in Mobile Networks. 2019 International Conference on Networked Systems (NetSys) (2019).
The requirements for video streaming have changed drastically during the past years. In today's Internet, high definition resolutions are considered default for videos, even in mobile settings, and with 4G penetration reaching 90 percent in the US, this no longer poses a big problem. However, while mobile bandwidth has increased, the battery life time of mobile devices has not increased significantly. Furthermore, current data plans are still not large enough to regularly stream movies during the commute. Users still resort to downloading media before travel. In this paper we propose a new HTTP adaptive streaming algorithm that delivers videos in high quality while avoiding stalling events, schedules the download of video segments so that a energy conserving idle state is often reached and keeps the buffer low at points in the video where many viewers abandon the video to save data. While most adaptive streaming algorithms optimize quality and stalling, this is the first attempt to use an adaptive streaming algorithm to reduce energy consumption. Since video streaming providers mostly care about the Quality of Experience when watching videos, energy efficiency is left to the device manufacturers. Therefore, both parties have little incentive to cooperate in this regard. But on the Internet of tomorrow, where most videos are watched on mobile devices, energy efficiency and the Quality of Experience must go hand in hand.
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Grigorjew, A., Metzger, F., Hoßfeld, T., Specht, J.: A Simulation of Asynchronous Traffic Shapers in Switched Ethernet Networks. Workshop for Advanced Communication Networks for Industrial Applications (2019).
As the requirements of real-time networking in- crease, the IEEE Time-Sensitive Networking (TSN) task group is working on new standards for high bandwidth and low latency Ethernet switching. In particular, the upcoming P802.1Qcr standard features Asynchronous Traffic Shaping (ATS), which is a promising approach for real-time networks with high dynamics and critical safety requirements. Additionally, parallel concepts such as frame preemption can be used to reduce delays even further. This work presents a discrete event simulation framework that can analyze the performance of these concepts. It implements frame preemption and multiple shaping algorithms, while recording latency and queue utilization statistics at the switches. In addition, an evaluation of a linear topology with four switches is performed under high link utilization, which demonstrates the benefit of the above mechanisms compared to regular Ethernet switching.
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Hirth, M., Steurer, F., Borchert, K., Dubiner, D.: Task Scheduling on Crowdsourcing Platforms for Enabling Completion Time SLAs. 31st International Teletraffic Congress (ITC). , Budapest, Hungary (2019).
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Geißler, S., Prantl, T., Lange, S., Wamser, F., Hoßfeld, T.: Discrete-Time Analysis of the Blockchain Distributed Ledger Technology. 31st International Teletraffic Congress (ITC). , Budapest, Hungary (2019).
Blockchain and distributed ledger technologies have become more and more popular and widespread during recent years. After the initial hype about the technology and many cryptocurrency related use cases, the technology slowly starts to make its way into other domains like food tracking and document management. In order to further contribute to the search of what this technology can be used for, more detailed performance evaluations are required in order to investigate key performance indicators and general limits of the technology. To this end, we develop a discrete-time queueing model that allows a detailed evaluation of the characteristics of a blockchain system, such as the transaction waiting time distribution. Furthermore, we validate the model by comparing the results to values obtained from measurements in a closed lab environment based on the Ethereum blockchain.
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Moldovan, C., Wamser, F., Hoßfeld, T.: User Behavior and Engagement of a Mobile Video Streaming User from Crowdsourced Measurements. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX) (2019).
Mobile video streaming has gained a lot of popularity in recent year with the introduction of large data plans for mobile phones. While users in non-mobile scenarios have become accustomed to high quality and few stalling events, this is not the case in mobile environments. People are more likely to tolerate stalling since they know high throughput coverage cannot always be guaranteed. Their behavior and their engagement are drastically different when watching videos on mobile devices. In this paper, we characterize mobile phone users who use a video streaming application. We present a data set of over 6,000 video views from a crowdsourced video measurement study. We investigate user activity and engagement during video streaming and how such metrics are correlated with each other. This is the first study that goes beyond user engagement and investigates the direct behavior of mobile video users outside the lab which is an important step towards mobile QoE management.
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Gray, N., Grigorjew, A., Hoßfeld, T., Shukla, A., Zinner, T.: Gray, Nicholas, et al. "Highlighting the Gap Between Expected and Actual Behavior in P4-enabled Networks. IFIP/IEEE Symposium on Integrated Network and Service Management (IM) (2019).
Modern networks increasingly rely on Software-defined Networking (SDN) and Network Function Virtualization (NFV) to augment their flexibility in high load scenarios. To further enhance the performance, a part of the functionality is often offloaded to forwarding devices, which are used as hardware accelerators and are configured by high level programming languages such as P4. However, hardware vendors use sophisticated technologies to implement these standards, which need to be understood by the programmer to avoid unintended behavior. In this demonstration we highlight the severe consequences of only relying on the network programming language when ignoring the device-specific limitations. We show this by the example of a Denial of Service attack against a P4-enabled SmartNIC. Finally, we discuss possible mitigations to this attack and stress the importance of an overall understanding of the entire system.
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Loh, F., Wamser, F., Moldovan, C., Zeidler, B., Hoßfeld, T., Tsilimantos, D., Valentin, S.: From click to playback: a dataset to study the response time of mobile YouTube. Proceedings of the 10th ACM Multimedia Systems Conference. pp. 267-272 (2019).
Responding fluently to user requests is important to keep them immersed. In this paper, we are presenting an extensive dataset to study the response time of YouTube's mobile video streaming service on Android. We illustrate the application of our dataset by studying YouTube's initial delay for a subset of 9 videos in 75 network scenarios. We find that in 41% of the cases, YouTube exceeds the attention span of a typical user, while deep immersion is only reached in 15% of the cases. Our factor analysis implies that the allocation of the initial CDN node is the critical link in this delay chain. Since our dataset includes a large variety of factors, we are describing setup, methodology, and data structure in detail. Our dataset and measurement tools are publicly available.
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Orsolic, I., Skorin-Kapov, L., Hoßfeld, T.: To Share or Not to Share? How Exploitation of Context Data Can Improve In-Network QoE Monitoring of Encrypted YouTube Streams. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX) (QoMEX 2019) (2019).
With the widespread use of encryption in Over the Top (OTT) traffic, Internet Service Providers (ISPs) for the most part lack insights into application performance, as well as into Quality of Experience (QoE) perceived by end users. Addressing challenges related to encryption, ISPs are looking into machine learning based solutions that can detect application performance solely from statistical properties of the traffic. On the other hand, OTT service providers are not willing to share service performance and content-related information with ISPs. While related work on OTT-ISP collaboration scenarios has addressed architectural aspects, business models, and to a certain extent incentives for sharing data, the focus of this paper is on the exchanged data itself. We investigate to what extent the performance of in-network machine learning based QoE estimation models for HTTP adaptive video streaming could be improved with the availability of certain context data provided by OTT providers. We motivate OTT-ISP collaboration through more accurate in-network QoE monitoring and potential improvement of user experience, which is of interest to both sides.
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Hirth, M., Borchert, K., Allendorf, F., Metzger, F., Hoßfeld, T.: Crowd-based Study of Gameplay Impairments and Player Performance in DOTA 2. 4th Internet-QoE Workshop: QoE-based Analysis and Management of Data Communication Networks (Internet-QoE'19). , Los Cabos, Mexico (2019).
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Wassermann, S., Seufert, M., Casas, P., Li, G., Kuang, L.: I See What you See: Real Time Prediction of Video Quality from Encrypted Streaming Traffic. 4th Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Los Cabos, Mexico (2019).
We address the problem of real-time QoE monitoring of HAS, from the ISP perspective, focusing in particular on videoresolution analysis. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to predict different video resolution levels in a fine-grained scale, ranging from 144p to 1080p resolution, using as input only packet-level data. The proposed measurement system performs predictions in real time, during the course of an ongoing video-streaming session, with a time granularity as small as one second. We consider the particular case of YouTube video streaming. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements demonstrate that the proposed system can predict video resolution with very high accuracy, and in real time. Different from state of the art, the prediction task is not bound to coarse-grained video quality classes and does not require chunk-detection approaches for feature extraction.
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Schwind, A., Haberzettl, L., Wamser, F., Hoßfeld, T.: QoE Analysis of Spotify Audio Streaming and App Browsing. 4th Internet-QoE Workshop: QoE-based Analysis and Management of Data Communication Networks (Internet-QoE'19) (2019).
Spotify is the most-listened audio streaming provider in 2019 with 217 million active users per month. Providers are therefore interested in the quality and functionality of Spotify in order to provide their users with the best possible streaming quality. While video streaming services such as Netflix and their streaming approach have been extensively explored in previous research, audio streaming services like Spotify and their corresponding behavior at certain network conditions have not been considered in detail yet. In this paper, we perform a QoE analysis under various network conditions and examine the app browsing performance of the audio streaming platform Spotify using its native Android mobile application. We have developed a measurement tool that emulates a user listening to audio through Spotify. While streaming, application and network layer parameters are captured that have a high correlation to the user’s QoE. The paper shows a baseline scenario including the streaming of a single song as well as playlist streaming behavior. Next, the effect of interruptions on the streaming behavior is evaluated and finally, the influence of network impairments on QoE key performance indicators such as initial delay is shown.
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Wamser, F., Tran-Gia, P., Geißler, S., Hoßfeld, T.: Modeling of Traffic Flows in Internet of Things Using Renewal Approximation. International Conference on Optimization and Decision Science (ODS2019) (2019).
This paper proposes a versatile approach to model aggregated traffic flows in the Internet of Things (IoT) using renewal approximation. The modeled traffic originates from a large number of sources or devices consisting of a set of sensors mixed with classical elastic random traffic modeled as Poisson arrival process. The work shows the exact derivation in the simple case for periodic sensors. It shows further results in the mixed case with periodic sensors and a background process. The renewal approximation allows to derive the required number of sensors such that the aggregated traffic can be approximated as Poisson process.
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Wassermann, S., Casas, P., Seufert, M., Wamser, F.: On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements. 12th IFIP Wireless and Mobile Networking Conference (WMNC). , Paris, France (2019).
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Schwind, A., Janiak, L., Moldovan, C., Wamser, F., Hoßfeld, T.: Peeking under the Hood – How the Measurement Setup Influences the Video Streaming Behavior. The 3rd International Workshop on Quality of Experience Management (QoE-Management 2019). , Paris, France (2019).
Global Internet video traffic will dramatically increase in the next years. With this rapid growth, interest in the application behavior of video streaming services and the resulting user experience rises. In particular, there is a need to understand the influence of system parameters on the streaming performance. Thus, several monitoring approaches have been developed which allow conducting automated measurements on a large-scale, for example, lightweight approaches for measurements running in the mobile networks or setups using a virtual frame buffer for servers without a display running in virtualized cloud environments. In some cases, the measurement hardware can totally be controlled, in other cases, there is no knowledge about parallel running services. In this paper, we answer the question whether and how much the measurement setup (e.g., virtualization, headless browsers, load on machines) influences the video streaming behavior. Therefore, we compare eight management setups with the ground truth (an end user watching a video on the own device) by evaluating the key performance indicators on application layer during video streaming, i.e. initial video playout delays and stalling. Our results reveal important insights: some of the common measurement setups heavily influence the measurements and must be avoided to collect reliable results.
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Enghardt, T., Zinner, T., Feldmann, A.: Web Performance Pitfalls. Passive and Active Measurement Conference (PAM) (2019).
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Hoßfeld, T., Atzori, L., Heegaard, P.E., Skorin-Kapov, L., Varela, M.: The Interplay between QoE, User Behavior and System Blocking in QoE Management. 22nd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN) (2019).
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Alissa, A., Bentalab, A., Zinner, T., Ghita, B., Mkwawa, I.-H.: BBGDASH: A Max-Min Bounded Bitrate Guidance for SDN Enabled Adaptive Video Streaming. 22nd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN (2019).
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Schwarzmann, S., Breitbach, P., Zinner, T.: Computing QoE-relevant Adaptive Video Streaming Metrics using Discrete-Time Analysis. Third International Workshop on Quality of Experience Management 2019 (2019).
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Lange, S., Linguaglossa, L., Geißler, S., Rossi, D., Zinner, T.: Discrete-Time Modeling of NFV Accelerators that Exploit Batched Processing. IEEE Conference on Computer Communications (Infocom) (2019).
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Geißler, S., Lange, S., Wamser, F., Zinner, T., Hoßfeld, T.: KOMon - Kernel-based Online Monitoring of VNF Packet Processing Times. 2019 International Conference on Networked Systems (NetSys), Best Paper Award (2019).
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Borchert, K., Hirth, M., Stellzig-Eisenhauer, A., Kunz, F.: Crowd-based Assessment of Deformational Cranial Asymmetries. International Workshop on Crowd-Powered e-Services (CROPS). , Trondheim, Norway (2019).
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Seufert, M., Casas, P., Wehner, N., Li, G., Kuang, L.: Stream-based Machine Learning for Real-time QoE Analysis of Encrypted Video Streaming Traffic. 3rd International Workshop on Quality of Experience Management (QoE-Management). , Paris, France (2019).
As stalling is the worst Quality of Experience (QoE) degradation of HTTP adaptive video streaming (HAS), this work presents a stream-based machine learning approach, ViCrypt, which analyzes stalling of YouTube streaming sessions in real-time from encrypted network traffic. The video streaming session is subdivided into a stream of short time slots of 1 s length, while considering two additional macro windows each for the current streaming trend and the whole ongoing streaming session. Constant memory features are extracted from the encrypted network traffic in these three windows in a stream-based fashion, and fed into a random forest model, which predicts whether the current time slot contains stalling or not. The presented system can predict stalling with a very high accuracy and the finest granularity to date (1 s), and thus, can be used in networks for real-time QoE analysis from encrypted YouTube video streaming traffic. The independent predictions for each consecutive slot of a streaming session can further be aggregated to obtain stalling estimations for the whole session. Thereby, the proposed method allows to quantify the initial delay, as well as the overall number of stalling events and the stalling ratio, i.e., the ratio of total stalling time and total playback time.
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Seufert, M., Schatz, R., Wehner, N., Casas, P.: QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning. 3rd International Workshop on Quality of Experience Management (QoE-Management). , Paris, France (2019).
The introduction of the QUIC (Quick UDP Internet Connections) transport protocol by Google aimed to improve the Quality of Experience (QoE) with web services compared to the prevailing Transport Control Protocol (TCP). Nowadays, QUIC has become the default protocol to communicate between the Google Chrome browser and Google servers and accounts for an increasing share of the Internet traffic. This work investigates whether the promised QoE benefits of QUIC are indeed noticeable for end users or not. A measurement study was conducted for YouTube video streaming in two mobile and two fixed access networks, in which a defined set of videos was streamed back-to-back with QUIC and TCP in randomized order. QoE factors of video streaming (such as initial delay, the visual quality of the video, and stalling) were compared statistically to find significant differences between the streaming over QUIC and the streaming over TCP. Surprisingly, no evidence for any QoE improvement of QUIC over TCP in the context of YouTube streaming could be found.
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Borchert, K., Schwind, A., Hirth, M., Hoßfeld, T.: In Vivo or in Vitro? Influence of the Study Design on Crowdsourced Video QoE. 11th International Conference on Quality of Multimedia Experience (QoMEX) (2019).
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Seufert, M., Casas, P., Wehner, N., Li, G., Kuang, L.: Features that Matter: Feature Selection for On-line Stalling Prediction in Encrypted Video Streaming. 2nd International Workshop on Network Intelligence (NI). , Paris, France (2019).
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Maggi, L., Leguay, J., Seufert, M., Casas, P.: Online Detection of Stalling and Scrubbing in Adaptive Video Streaming. 17th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt). , Avignon, France (2019).
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Seufert, M., Schatz, R., Wehner, N., Gardlo, B., Casas, P.: Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE. 11th International Conference on Quality of Multimedia Experience (QoMEX). , Berlin, Germany (2019).
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Seufert, M.: Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores. 11th International Conference on Quality of Multimedia Experience (QoMEX). , Berlin, Germany (2019).
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Loh, F., Vomhoff, V., Wamser, F., Metzger, F., Hoßfeld, T.: Traffic Measurement Study on Video Streaming with the Amazon Echo Show. 4th Internet-QoE Workshop: QoE-based Analysis and Management of Data Communication Networks (2019).
The Amazon Echo Show is one of the most widely used smart speakers with the ability to stream video. Due to its popularity, the traffc profiles of such devices are of interest to network operators and providers. This work presents a measurement study of the Amazon Echo Show in terms of network traffc and streaming behavior. More than 470 hours of streaming data are collected and analyzed at network layer. Based on this, streaming quality is derived at application layer. The study quantifies the traffc and shows that streaming with the Amazon Echo Show is comparable to streaming with a native web browser, but in a more conservative way.
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Lagerspetz, E., Flores, H., Mäkitalo, N., Hui, P., Nurmi, P., Tarkoma, S., Passarella, A., Ott, J., Reichl, P., Conti, M., Fiedler, M., Singh, J., Strufe, T., Hoßfeld, T.: Pervasive Communities in the Internet of People. Proceedings of the 1st International Workshop on Context-Awareness for Multi-Device Pervasive and Mobile Computing (PerCrowd). , Athens, Greece (2018).
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Seufert, M., Wehner, N., Casas, P.: Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203. 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Vienna, Austria (2018).
P.1203 is a recent standardized model for assessing the Quality of Experience (QoE) of HTTP Adaptive Video Streaming (HAS). However, its complex definition does not allow for a straightforward identification of the underlying assumptions. To overcome this issue, this work investigates the impact of the well-known QoE factors of HAS, namely, initial delay, stalling, and adaptation, on the output QoE score of the model. Therefore, parameter studies are conducted using a reference implementation of P.1203, and the model response to variations of the input QoE factors are compared to results of previous QoE studies in order to get a deeper understanding of the standardized model and its inherent weighting of the QoE factors of HAS.
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Yang, J., van der Valk, C., Hoßfeld, T., Redi, J., Bozzon, A.: How do crowdworker communities and microtask markets influenceeach other? A data-driven study on Amazon Mechanical Turk. Sixth AAAI Conference on Human Computation and Crowdsourcing (2018).
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Volodina, E., Aziz, A., Rathgeb, E., Hoßfeld, T.: Application of Visual Analysis to Detect and Analyze Patterns in VoIP Attack Traffic. 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) (2018).
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Grigorjew, A., Gray, N., Hoßfeld, T., Shukla, A., Zinner, T.: Bridging the Gap Between Programming and Implementation of Networking Devices. Student Workshop of the 14th International Conference on emerging Networking EXperiments and Technologies (2018).
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Voigt-Antons, J.-N., Hoßfeld, T., Egger-Lampl, S., Schatz, R., Möller, S.: User Experience of Web Browsing-The Relationship of Usability and Quality of Experience. Tenth International Conference on Quality of Multimedia Experience (QoMEX) (2018).
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Tran, H.T.T., Pham Ngoc, N., Hoßfeld, T., Thang, T.C.: A Cumulative Quality Model for HTTP Adaptive Streaming. Tenth International Conference on Quality of Multimedia Experience (QoMEX) (2018).
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Flittner, M., Bauer, R., Rizk, A., Geissler, S., Zinner, T., Zitterbart, M.: Taming the complexity of artifact reproducibility. Proceedings of the Reproducibility Workshop (2018).
Reproducing research results, as it is required for peer review, can be a time-consuming and difficult task. In this work, we propose three approaches to improve the way of how research results can be substantiated and discuss their applicability. Our proposals are based on a brief study on evaluation methods (for SDN research) and insights from a comprehensive discussion on reproducibility.
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Hoßfeld, T., Varela, M., Heegaard, P.E., Skorin-Kapov, L.: Observations on Emerging Aspects in QoE Modeling and Their Impact on QoE Management. 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX) (2018).
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Zach, O., Slanina, M., Seufert, M.: Investigating the Impact of Advertisement Banners and Clips on Video QoE. 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Vienna, Austria (2018).
Although Quality of Experience (QoE) of Internet services can be affected by context influence factors, their actual impact is not widely investigated yet. In the context of online video services, web portals often display advertisement banners or clips to monetize their service. However, these advertisements can distract or annoy the users, which might degrade the QoE of the actual video service. In this work, two crowdsourcing studies were conducted to investigate the impact of advertisement banners and clips on video QoE. Therefore, both theoretical opinions on in-service advertisements and subjective quality ratings are evaluated. The findings confirm that advertisements are negatively perceived by users during service consumption, but a generally negative impact on video QoE cannot be supported, as the interplay of advertisement and the QoE of video services is rather complex.
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Grigorjew, A., Lange, S., Zinner, T., Tran-Gia, P.: Performance Benchmarking of Network Function Chain Placement Algorithms. 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB) (2018).
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Seufert, M., Tran-Gia, P.: Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming. IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award. , Taipei, Taiwan (2018).
The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.
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Karagkioules, T., Tsilimantos, D., Valentin, S., Wamser, F., Zeidler, B., Seufert, M., Loh, F., Tran-Gia, P.: A Public Dataset for YouTube’s Mobile Streaming Client. Network Traffic Measurement and Analysis Conference (TMA). , Vienna, Austria (2018).
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Wassermann, S., Wehner, N., Casas, P.: Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones. Workshop on AI in Networks (WAIN) (2018).
Measuring and monitoring YouTube Quality of Experience is a challenging task, especially when dealing with cellular networks and smartphone users. Using a large-scale database of crowdsourced YouTube-QoE measurements in smartphones, we conceive multiple machine-learning models to infer different YouTube-QoE-relevant metrics and user-behavior-related metrics from network-level measurements, without requiring root access to the smartphone, video-player embedding, or any other reverse-engineering-like approaches. The dataset includes measurements from more than 360 users worldwide, spanning over the last five years. Our preliminary results suggest that QoE-based monitoring of YouTube mobile can be realized through machine learning models with high accuracy, relying only on network-related features and without accessing any higher-layer metric to perform the estimations.
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Iffländer, L., Geißler, S., Walter, J., Beierlieb, L., Kounev, S.: Addressing Shortcomings of Existing DDoS Protection Software Using Software-Defined Networking. 9th Symposium on Software Performance 2018 (SSP'18). , Hildesheim, Germany (2018).
DDoS attacks are becoming increasingly frequent and violent. A typical type of attack is the TCP SYN flood, inhibiting a server from opening new TCP connections. Current countermeasures to this attack introduce inefficiencies by either reducing computing resources on the service host or creating new network bottlenecks. In this work, we present a novel approach to mitigate TCP SYN flood attacks using software-defined networking. We perform an initial evaluation of a proof-of-concept implementation that exhibits performance measures close to existing countermeasures while circumventing their inefficiencies.
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Seufert, M., Schwind, A., Waigand, M., Hoßfeld, T.: Potential Traffic Savings by Leveraging Proximity of Communication Groups in Mobile Messaging. 14th International Conference on Network and Service Management (CNSM). , Rome, Italy (2018).
Communication groups in mobile messaging applications (MMAs) multiply the data transmissions, because every message has to be delivered to all members of the communication group. Thereby, they put a high load on mobile networks. As the number of recipients is still comparably small, the dataintensive user-generated content cannot be handled efficiently in large content delivery networks. However, small communication groups, such as groups of friends or teams, might often be in close proximity, which can be leveraged to locally deliver messages by applying edge caching or device-to-device (D2D) communication. In this work, a simulation study is conducted to investigate these potential traffic savings in the mobile network. It is based on a realistic communication model of the MMA WhatsApp and utilizes different models for human mobility. The user mobility and MMA communication are simulated for a single day in a small city to obtain the ratio of messages, which could be potentially transmitted locally when utilizing edge caching and D2D communication.
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Metter, C., Burger, V., Hu, Z., Pei, K., Wamser, F.: Evaluation of the Detection Capabilities of the ONOS SDN Controller. 7th IEEE International Conference on Communications and Electronics (IEEE ICCE 2018). pp. 96 - 101. , Hue, Vietnam (2018).
The process of monitoring the network, especially for larger ones, is very complex and contains many pitfalls. For instance the balance between granularity of information and their performance impact on the network. With the help of SDN this challenge can become easier, as it offers new methods, mechanisms and opportunities. One of the current most important Open Source controllers is the ONOS SDN controller. According to its developers it is a production ready controller that offers high availability due to its logically centralized and physically distributed architecture. But, as our investigations show, it is unable to cope with hazardous network conditions such as sporadic or recurring packet loss. It either does not detect packet loss or only detects it after long time periods, failing all common network availability targets.
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Wehner, N., Wassermann, S., Casas, P., Seufert, M., Wamser, F.: Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE. 14th International Conference on Network and Service Management (CNSM). , Rome, Italy (2018).
Measuring the Quality of Experience (QoE) undergone by cellular network users has become paramount for cellular ISPs. Given its overwhelming dominance and ever-growing popularity, this paper focuses on the analysis of QoE for YouTube in mobile networks. Using a large-scale dataset of crowdsourced YouTube QoE measurements collected in smartphones with YoMoApp, we analyze the evolution of multiple relevant QoE-related metrics over time for YouTube mobile users. The dataset includes measurements from more than 360 users worldwide, spanning over the last five years. Our data-driven analysis shows a systematic performance and QoE improvement of YouTube in mobile devices over time, accompanied by an improvement of cellular network performance and by an optimization of the YouTube streaming behavior for smartphones.
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Seufert, M., Wehner, N., Casas, P., Wamser, F.: A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming. 14th International Conference on Network and Service Management (CNSM), Best Paper Award. , Rome, Italy (2018).
This paper presents a novel adaptation logic for HTTP adaptive streaming (HAS), which achieves not only a high Quality of Experience (QoE) but also high QoE fairness among independent and heterogeneous clients. The algorithm forces video clients to adapt the requested quality level based on the current network conditions and their individual bit rate requirements, such that the overall quality levels selected by all currently active streaming clients are fairly distributed, i.e., they do not diverge too much. The design of the algorithm is inspired by the well-known Transmission Control Protocol (TCP) congestion control, and drives heterogeneous clients to independently converge on similar quality levels without the need for communicating with each other and/or with a centralized controller in the network. By defining quality levels with equal visual quality, and preparing video representations accordingly, the quality level fairness is extended to QoE fairness. In this work, the design of the algorithm is described and a simulative performance evaluation is conducted to compare the QoE and QoE fairness of the proposed algorithm with other HAS adaptation logics.
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Metter, C., Burger, V., Hu, Z., Pei, K., Wamser, F.: Towards an Active Probing Extension for the ONOS SDN Controller. 2018 28th International Telecommunication Networks and Applications Conference (ITNAC) (ITNAC 2018). p. 8. , Sydney, Australia (2018).
Network monitoring is a complex task and is always a trade-off between granularity of information and the performance impact of the monitoring itself on the network. SDN controllers, such as the ONOS SDN controller make this challenge easier as they can supply centralized information over the whole network. In our previous work we mathematically analyzed the built-in detection mechanism of ONOS and revealed a lack of detection performance and the vulnerability of this process to jitter. These results were also verified by measurements. In this paper we present an Active Probing extension for the ONOS SDN controller that overcomes these shortcomings by emitting probing packets that are transmitted through the network. Statistics over a history of those packets allow for the detection of packet loss. The evaluation by the means of measurements proves the benefits in terms of detection performance and controller load of this application. Furthermore, our extension is able to detect jitter being present in the network and to automatically adapt the probing process to these conditions.
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Hoßfeld, T., Metzger, F., Heegaard, P.E.: Traffic Modeling for Aggregated Periodic IoT Data. Proceedings of the 21st Conference on Innovation in Clouds, Internet and Networks (ICIN). , Paris, France (2018).
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Borchert, K., Lange, S., Zinner, T., Hirth, M.: Identification of Delay Thresholds Representing the Perceived Quality of Enterprise Applications. The 2nd International Workshop on Quality of Experience Management. , Sardinia, Italy (2018).
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Surminski, S., Moldovan, C., Hoßfeld, T.: Practical QoE Evaluation of Adaptive Video Streaming. Proceedings of the 19th International Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB). , Erlangen, Germany (2018).
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Hoßfeld, T., Varela, M., Heegaard, P.E., Skorin-Kapov, L.: QoE Analysis of the Setup of Different Internet Services for FIFO Server Systems. Proceedings of the 19th International Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB). , Erlangen, Germany (2018).
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Nguyen-Ngoc, A., Lange, S., Geissler, S., Zinner, T., Tran-Gia, P.: Estimating the Flow Rule Installation Time of SDN Switches when Facing Control Plane Delay. 19th International GI/ITG Conference on “Measurement, Modelling and Evaluation of Computing Systems”. , Erlangen (2018).
The software defined networking (SDN) paradigm has numerous benefits for network operators, including cost aspects, flexibility, and programmability. In the centralized SDN architecture, the controller can order the installation of flow rules in the switches it manages via FlowMod messages. Since the processing time of these messages has a direct impact on the reaction time of the network, it is a key performance indicator for switches and quantifying it in a reliable manner is required for ensuring state consistency between the control and the data plane. Furthermore, real world deployments not only consist of different data plane hardware, but may feature varying control plane delays. Hence, in this work, we investigate the impact of such a delay on the FlowMod processing time of OpenFlow switches. Firstly, we identify a significant heterogeneity between data plane hardware in terms of processing times as well as the underlying TCP-level behavior. Secondly, we show that despite this heterogeneity, combining switch specific information with delay measurements at the controller can be used to reliably infer FlowMod processing times. We confirm our results with measurements in a dedicated testbed that is comprised of three different hardware switches, three different SDN controllers, and several high precision measurement devices.
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Metzger, F., Heger, R.: Exploring the Transmission Behaviour of Overwatch: The Source of Lag. 30th International Teletraffic Congress (ITC 30) (2018).
This paper explores the full chain of lag contribution factors in a specific online multiplayer game, namely Overwatch: From creating input events over the network and back to displaying the results on the local screen. Together result in the dreaded end-to-end lag. which has a direct impact on the subjective quality one experiences when playing video games. In its investigation, this paper reveals surprising effects in the game's networking behavior that are omitted when colloquially talking about, e.g. a 60 Hz update rate, but must be considered nonetheless. These insights, gained from examining network traces of Overwatch matches that were played on a realistic, resource constrained PC, can then be used to refine end-to-end lag simulation models and reach a better understanding of all responsible components.
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Hoßfeld, T., Metzger, F., Rossi, D.: Speed Index: Relating the Industrial Standard for User Perceived Web Performance to Web QoE. Proceedings of the 10th International Conference on Quality of Multimedia Experience (QoMEX 2018). , Sardinia, Italy (2018).
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Seufert, M., Zeidler, B., Wamser, F., Karagkioules, T., Tsilimantos, D., Loh, F., Tran-Gia, P., Valentin, S.: A Wrapper for Automatic Measurements with YouTube's Native Android App. Network Traffic Measurement and Analysis Conference (TMA). , Vienna, Austria (2018).
YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.
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Lange, S., Reinhart, L., Zinner, T., Hock, D., Gray, N., Tran-Gia, P.: Integrating Network Management Information into the SDN Control Plane. IEEE/IFIP Network Operations and Management Symposium (NOMS) (2018).
With software defined networking (SDN), operators benefit from a higher flexibility, cost efficiency, as well as programmability of their networks. Since modern networks are comprised of a multitude of heterogeneous devices and also include non-SDN legacy devices, network management systems (NMSs) are often used in order to monitor and configure the network. Although both, the SDN controller and the NMS, have a centralized view of the network, they operate at different time scales and deal with information at different levels of granularity. In this work, we investigate the impact on the network performance when an NMS regularly provides information to an SDN controller. To this end, we design, implement, and compare three interaction mechanisms based on the ONOS controller. These represent different trade-offs regarding the complexity of the resulting system and its performance. In addition to the default ONOS controller, we develop two extended versions. One performs hash-based load balancing on equal cost paths while the other utilizes external NMS information via ONOS's intent and annotation framework to optimize control plane decisions. In addition to evaluations that show a significant performance improvement when using the optimized controllers, we present a parameter study that highlights the performance impact of network characteristics like the flow interarrival time, the flow duration, and the number of active flows.
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Schwarzmann, S., Zinner, T., Sieber, C., Geißler, S.: Evaluation of the Benefits of Variable Segment Durations for Adaptive Streaming. The 2nd International Workshop on Quality of Experience Management. , Sardinia, Italy (2018).
HTTP Adaptive Streaming (HAS) is the de-facto standard for video delivery over the Internet. It enables the dynamic adaptation of video quality by splitting the video clip into small segments and providing multiple quality levels per segment. Current HAS streaming services typically utilize segments of equal durations. However, this leads to video encoding overhead as segments have to start with I-frames, independently of the encoded video content. In this paper we evaluate the prospects of variable segment durations, where video segments are aligned to the video characteristics. We evaluate the reduction of the encoding overhead and investigate its impact on the stalling probability using a theoretical model. It turns out that the variable approach outperforms the fixed approach in 86% of the evaluated cases with respect to video stalls.
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Gray, N., Lange, S., Zinner, T., Pfaff, B., Hock, D.: Evaluation of a Distributed Control Plane for Managing Heterogeneous SDN-enabled and Legacy Networks. 7th International Conference on Communications and Electronics (ICCE). , Hue, Vietnam (2018).
With the increasing number of devices, protocols and applications, today’s networks are becoming more and more complex. Hence, Software-defined Networking (SDN) tries to ad- dress this issue by separating the data from the control plane and by providing centralized interfaces for network configuration. As legacy devices cannot be replaced instantly due to high costs, both network segments have to be operated in coexistence with defined joints at their edges. To ensure a smooth operation, both controlling instances of these segments are required to exchange information. In this work, we design and implement a data model for storing the information needed to keep the controller and a Network Management System (NMS) synchronized, which are responsible for configuring the SDN-enabled network and the legacy devices respectively. For this, we implement and evaluate a total of three different synchronization strategies by the example of an SDN-based Bring Your Own Device (BYOD) use case. Index Terms—SDN, NMS, Management, Integration, Hetero- geneous Networks, Distributed Control Plane.
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Hirth, M., Lange, S., Seufert, M., Tran-Gia, P.: Performance Evaluation of Mobile Crowdsensing for Event Detection. Proceedings of the 5th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications. , Athens, Greece (2018).
Crowdsensing offers a cost effective way to collect large amounts of sensor data. However, in contrast to fixed sensor deployments, the spatial distribution of the sensors can hardly be influence, as the sensors are carried by participants of the crowdsensing system. This in turn raises the question about the performance of such systems with respect to the detection probability and detection time of spatial events. In order to address this question, we analyze the performance of such a crowdsensing system by means of simulation. We use the traffic infrastructure of a small size city in Germany and simulate the inhabitants’ movement patterns with the well established SUMO mobility generator. Our results show that even if only a small share of inhabitants participates in crowdsensing, events, which have locations that are correlated with the population density, can be easily and quickly detected using such a system. On the contrary, events whose locations are uniformly randomly distributed are much harder to detect using a crowdsensing approach.
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Schwind, A., Wamser, F., Gensler, T., Seufert, M., Casas, P., Tran-Gia, P.: Streaming Characteristics of Spotify Sessions. The 2nd International Workshop on Quality of Experience Management. , Sardinia, Italy (2018).
Internet Service Providers need a thorough understanding of a service to maximize the Quality of Experience (QoE) of their customers by network management. Instead of quantifying the user satisfaction with long and cost-intensive subjective user studies, the QoE can often be estimated with the help of dedicated measurements of application and network parameters. We designed a QoE measurement tool for the popular audio streaming service Spotify that runs inside a Docker software container. The container is able to run headlessly as active measurement probe and emulates a user who is streaming audio files via Spotify. While streaming, network and application parameters are collected that have a high correlation to the user's QoE. The results of the measurements are used to characterize audio streaming in Spotify on application and network layer, and to evaluate important QoE factors.
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Casas, P., Seufert, M., Wehner, N., Schwind, A., Wamser, F.: Enhancing Machine Learning based QoE Prediction by Ensemble Models. 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Vienna, Austria (2018).
The number of smartphones connected to wireless networks and the volume of wireless network traffic generated by such devices have dramatically increased in the last few years, making it more challenging to tackle wireless network monitoring applications. The high-dimensionality of network data provided by current smartphone devices opens the door to the massive application of machine learning approaches to improve different wireless networking applications. In this paper we study the specific problem of Quality of Experience (QoE) prediction for popular smartphone apps, using machine learning models and in-smartphone measurements. We evaluate and compare different models for the analysis of smartphone generated data, including single models as well as machine learning ensembles such as bagging, boosting and stacking. Results suggest that, while decision-tree based models are the most accurate single models to predict QoE, ensemble learning models, and in particular stacking ones, are capable to significantly increase accuracy prediction and overall classification performance.
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Dinh-Xuan, L., Seufert, M., Wamser, F., Vassilakis, C., Zafeiropoulos, A., Tran-Gia, P.: Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud. 30th International Teletraffic Congress (ITC30). , Vienna, Austria (2018).
The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.
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Wamser, F., Lombardo, C., Vassilakis, C., Dinh-Xuan, L., Lago, P., Bruschi, R., Tran-Gia, P.: Orchestration and Monitoring in Fog Computing for Personal Edge Cloud Service Support. 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN) (2018).
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Nguyen-Ngoc, A., Raffeck, S., Lange, S., Geißler, S., Zinner, T., Tran-Gia, P.: Benchmarking the ONOS Controller with OFCProbe. 7th International Conference on Communications and Electronics (ICCE). , Hue, Vietnam (2018).
The increased popularity of Software Defined Networking (SDN) drives the development and research of all involved components. In particular, state-of-the-art SDN controllers are a central part of the resulting network architecture and have a large impact on the performance of the entire network. Hence, it is necessary to quantify various performance indicators of the SDN controller in order to assess its feasibility in the context of different network characteristics such as topology and network size w.r.t. the number of nodes and links. To this end, we extend the open-source controller benchmarking tool OFCProbe with several novel modules that are capable of recording relevant performance metrics and demonstrate their use in the context of benchmarking the ONOS controller. Furthermore, we investigate the impact of different types of topology characteristics on the performance of the controller. In this work, we focus on several performance indicators for SDN controllers. First, the time that the ONOS controller needs to discover the network topology and update its internal representation of the topology. Second, we investigate the duration of the installation of flow rules that are used for reactive path provisioning. Finally, we measure the response time of the controller when dealing with asynchronous messages.
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Loh, F., Wamser, F., Hoßfeld, T., Tran-Gia, P.: Quality of Service Assessment of Live Video Streaming with a Remote-Controlled Drone. IEEE Conference on Network Softwarization. , Montreal, Canada (2018).
Today's networks require a deep understanding of applications to optimize networks, efficiently design networks, and meet traffic demands, application heterogeneity, and application requirements. Current application areas include live video streaming and real-time applications, such as those that are named in 5G use cases with automation, disaster recovery, gaming, and Industry 4.0. In this work, we examine an application scenario with live video streaming and parallel real-time requirements in the uplink for disaster recovery. We study the quality of service (QoS) features of a remote-controlled drone. The drone is controlled via a tablet or smartphone while the video from the camera is transmitted from the drone to the user. There are high demands in both the uplink and downlink direction. The contribution of the work is the measurement of the QoS and application parameters for this scenario and the definition of influencing parameters for the application-layer.
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Moldovan, C., Skorin-Kapov, L., Heegaard, P.E., Hoßfeld, T.: Optimal Fairness and Quality in Video Streaming With Multiple Users. 30th International Teletraffic Congress (ITC 30). p. 6. , Vienna, Austria (2018).
With the majority of video distribution services relying on the HTTP adaptive streaming paradigm, a great deal of research is geared towards developing algorithms and solutions for improving user perceived quality while making efficient use of available resources. Our goal is to provide the means for benchmarking such solutions in the context of multiple users accessing Video on Demand content while sharing a bottleneck link. For that purpose, we propose a quadratic problem formulation to compute the theoretical optimum in terms of adaptation strategies and corresponding segment downloads across multiple users under given bandwidth constraints. By aiming to maximize both service quality and fairness, we quantify and compare the impact of different fairness objectives (bandwidth fairness, pattern fairness, and session fairness) on resulting quality and achieved QoE fairness. Based on conducted simulations and parameter studies, our results demonstrate the benefits of optimizing for session fairness as compared to other approaches.
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Nguyen-Ngoc, A., Lange, S., Zinner, T., Seufert, M., Tran-Gia, P., Aerts, N., Hock, D.: Performance Evaluation of Selective Flow Monitoring in the ONOS Controller. 4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV). , Tokio, Japan (2017).
One of the benefits when network operators adopt the Software Defined Networking (SDN) paradigm is the ability to monitor the traffic in the network without an additional network management system. Usually, SDN controllers utilize OpenFlow statistics messages in order to regularly gather information about all flows in the network. However, using the same polling interval for all flows does not take into account the heterogeneity of real world traffic and thus results in an imbalance between monitoring accuracy and control plane overhead. In particular, frequent querying results in a high resource consumption at the controller. This work proposes a Selective Flow Monitoring (SFM) mechanism that allows administrators to classify flows according to their individual requirements in terms of monitoring frequency, e.g., less frequent polling of elephant flows and frequent polling of QoS sensitive VoIP connections. We compare the performance of the SFM mechanism with the default monitoring scheme in a testbed featuring the Open Network Operating System (ONOS) controller. In this context, the CPU utilization of the controller is used as performance indicator. After identifying relevant influence factors like the number of flows and switches in the network, we investigate the viability of the approaches in different scenarios. Finally, we provide guidelines regarding their choice.
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Lareida, A., Hoßfeld, T., Stiller, B.: The BitTorrent Peer Collector Problem. IFIP/IEEE International Symposium on Integrated Network Management. , Lisbon, Portugal (2017).
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Zach, O., Seufert, M., Hirth, M., Slanina, M., Tran-Gia, P.: On Use of Crowdsourcing for H.264/AVC and H.265/HEVC Video Quality Evaluation. Radioelektronika. , Brno, Czech Republic (2017).
Crowdsourcing has become a popular method in the field of video quality evaluation. Gathering the opinion of the users using crowdsourcing is quick and relatively cheap but such a study has to be designed very carefully in order to give relevant results. So far, the majority of the QoE studies using crowdsourcing has been focusing on the performance of H.264/AVC algorithm in different situations (such as encoder settings, stalling effects, etc). Modern video coding methods, however, are only rarely tested using the crowdsourcing approach. We designed a study comparing the performance of both H.264/AVC and H.265/HEVC standards in the crowdsourcing environment. We deal with the possibilities of delivering and presenting the HEVC encoded content to the participants of the crowdsourcing study and potential challenges. Finally, the study was performed using Microworkers platform and gathered results are then compared with three different objective video quality metrics.
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Hoßfeld, T., Fiedler, M., Gustafsson, J.: Betas: Deriving Quantiles from MOS-QoS Relations of IQX Models for QoE Management. IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management). , Lisbon, Portugal (2017).
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Seufert, M., Zach, O., Slanina, M., Tran-Gia, P.: Unperturbed Video Streaming QoE Under Web Page Related Context Factors. 9th International Conference on Quality of Multimedia Experience (QoMEX). , Erfurt, Germany (2017).
Quality of Experience (QoE) of Internet services is affected by human, system, and context influence factors. While most QoE studies so far are focused on system factors only, this work will assess the impact of context factors of video streaming on QoE. As video streaming is mostly consumed from web pages, such as video portals, the investigated test conditions are applied to the web page, which embeds the video player. Therefore, the study of context factors is implicitly conducted within a crowdsourced QoE study. The test conditions considered different page load times, poster image qualities, and displayed advertisements on the web page, which are typical context factors when consuming a video streaming service. The results of the study show that the modification of the context factors on the streaming web page leaves the users' QoE rating unperturbed, which suggests that the investigated context factors have a negligible impact on video streaming QoE, or that the rating task of the subjective QoE study superimposed the context factors.
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Casas, P., D'Alconzo, A., Wamser, F., Seufert, M., Gardlo, B., Schwind, A., Tran-Gia, P., Schatz, R.: Predicting QoE in Cellular Networks using Machine Learning and in-Smartphone Measurements. 9th International Conference on Quality of Multimedia Experience (QoMEX). , Erfurt, Germany (2017).
Monitoring the Quality of Experience (QoE) undergone by cellular network customers has become paramount for cellular ISPs, who need to ensure high quality levels to limit customer churn due to quality dissatisfaction. This paper tackles the problem of QoE monitoring, assessment and prediction in cellular networks, relying on end-user device (i.e., smartphone) QoS passive traffic measurements and QoE crowdsourced feedback. We conceive different QoE assessment models based on supervised machine learning techniques, which are capable to predict the QoE experienced by the end user of popular smartphone apps (e.g., YouTube and Facebook), using as input the passive in-device measurements. Using a rich QoE dataset derived from field trials in operational cellular networks, we benchmark the performance of multiple machine learning based predictors, and construct a decision-tree based model which is capable to predict the per-user overall experience and service acceptability with a success rate of 91% and 98% respectively. To the best of our knowledge, this is the first paper using end-user, in-device passive measurements and machine learning models to predict the QoE of smartphone users in operational cellular networks.
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Seufert, M., Wehner, N., Wamser, F., Casas, P., D'Alconzo, A., Tran-Gia, P.: Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp. 9th International Conference on Quality of Multimedia Experience (QoMEX). , Erfurt, Germany (2017).
YoMoApp (YouTube Monitoring App) is an Android app to monitor mobile YouTube video streaming on both application- and network-layer. Additionally, it allows to collect subjective Quality of Experience (QoE) feedback of end users. During the development of the app, the stable versions of YoMoApp were already available in the Google Play Store, and the app was downloaded, installed, and used on many devices to monitor streaming sessions. As the app was not advertised in special campaigns or used for dedicated QoE studies, the monitored streaming sessions of this period compose the data set of a large unsupervised field study. The collected data set is evaluated to characterize current mobile YouTube streaming on both application and network layers. Furthermore, the problems and methodology to obtain QoE results from such unsupervised field study are discussed together with the actual QoE results. Correlations between QoE factors are investigated, and the QoE of clusters of similar streaming sessions is analyzed.
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Moldovan, C., Burger, V., Metzger, F., Surminski, S., Hoßfeld, T.: Viability of Wi-Fi Caches in an Era of HTTPS Prevalence. 2017 IEEE International Conference on Communications Workshops (ICC Workshops). , Paris, France (2017).
Caches are often employed to better manage the ever-growing amount of global Internet traffic. Particularly, reverse proxies are often used to free up congested peering links and reduce inter-domain traffic. In addition, caches place content close to the edge, leading to lower latency which can be beneficial for many applications. In an effort to bring content even closer to end devices, home routers and public access points are now in the spotlight as a novel location for caches. Compared to CDNs, a Wi-Fi router only offers scarce storage and processing capabilities, putting an increased emphasis on resource management. In addition, a large share of traffic is transmitted through secured connections preventing the use of forward caches and other middle boxes. This paper strives to analyze how effective caching can be in public Wi-Fi routers. For this purpose, we conducted a field study with caches at public Wi-Fi hotspots in a field study. In addition, we present a queueing model for caches that we use to perform a mean-value analysis. We compare results from both methods in a performance analysis. Our results provide insights into difficulties of caching systems that are caused by an increase in the ratio of secured connections in the Internet.
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Seufert, M., Kamneng Kwam, B., Wamser, F., Tran-Gia, P.: EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim. 1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG). , Bologna, Italy (2017).
Edge cloud computing is a trending paradigm, which extends cloud computing by additionally utilizing computing resources at the network edge, e.g., at mobile base stations. Especially personalized services can be instantiated or migrated close to end users, which improves the latency and supports user mobility. However, the placement of the service chains is crucial for the performance of the services and the energy consumption of the edge cloud platform, and appropriate algorithms have to be designed. To support the simulative performance evaluation of such algorithms, EdgeNetworkCloudSim was developed. It is an extension of NetworkCloudSim, and allows to simulate and evaluate the orchestration and consolidation of service chains in an edge network cloud.
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Zinner, T., Geissler, S., Helmschrott, F., Burger, V.: Comparison of the Initial Delay for Video Playout Start for Different HTTP-based Transport Protocols. Workshop on Quality of Experience Management (2017).
This paper details a measurement study on the impact of different HTTP-based application layer protocols, namely HTTP/1, HTTP/2 and QUIC, on video streaming performance. In this context we evaluate the influence on the initial delay until video playout is started using the live version of the YouTube platform. Furthermore, we evaluate how different network parameters, i.e. bandwidth, RTTs and packet loss influence the different protocols. This work presents an verview over the characteristics of the compared protocols and presents a detailed measurement methodology on how the data has been obtained. Finally, the observed data is evaluated in the context of YouTube video streaming.
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Gray, N., Lorenz, C., Müssig, A., Gebert, S., Zinner, T., Tran-Gia, P.: A Priori State Synchronization for Fast Failover of Stateful Firewall VNFs. Workshop on Software-Defined Networking and Network Function Virtualization for Flexible Network Management (SDNFlex 2017). , Göttingen, Germany (2017).
Network Functions Virtualization (NFV) replaces physical middleboxes with software instances running network functions in cloud environments. To support this new paradigm, it is necessary to port the code basis from highly specialized hardware devices to virtual machines running on COTS hard- ware. In order to fully exploit the inherent capabilities of cloud environments it is further necessary to redesign the software to support a large amount of distributed, cooperating function instances instead of single, isolated and monolithic instances. This development can be observed for network functions like stateful firewalling. Until now, available software firewalls lack support for active/active operation in clustered environments, which hinders horizontal scalability. This is due to the fact that the required synchronization of connection states among the cluster’s instances is an impediment that still has to be resolved. Therefore, this work investigates different synchronization strategies and mechanisms, which allow to share connection states among the cluster to maintain scalability and high-availability
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Geissler, S., Gebert, S., Herrnleben, S., Zinner, T., Bauer, R., Jarschel, M.: TableVisor 2.0: Towards Full-Featured, Scalable and Hardware-Independent Multi Table Processing. NetSoft 2017, Best Student Paper Award (2017).
Modern Software Defined Networking (SDN) appli- cations rely on sophisticated packet processing. However, there is a mismatch between control plane requirements and data plane capabilities caused by increasing hardware heterogeneity. To overcome this challenge, we propose TableVisor, a proxy-layer for the OpenFlow control channel that enables the flexible and scalable abstraction of multiple physical devices into one emu- lated data plane switch that meets the requirements of the control plane application. TableVisor registers with the SDN controller as a single switch with use-case specific capabilities. It translates the instructions and rules from the control application towards the appropriate physical device where they are executed. In this paper, we present the updated architecture and functionality of TableVisor as well as first evaluation results based on testbed experiments.
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Dinh-Xuan, L., Seufert, M., Wamser, F., Tran-Gia, P.: Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF. 1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management). , Lisbon, Portugal (2017).
The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.
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Burger, V., Seufert, M., Zinner, T., Tran-Gia, P.: An Approximation of the Backhaul Bandwidth Aggregation Potential Using a Partial Sharing Scheme. 15th IFIP/IEEE International Symposium on Integrated Network Management (IM). , Lisbon, Portugal (2017).
To cope with the increasing demands of mobile devices and the limited capacity of cellular networks, mobile connections are offloaded to WiFi. The access capacity is further increased by aggregating backhaul bandwidth of WiFi access links. To analyze the performance of aggregated access links we develop a model for two and more cooperating systems sharing capacities using an offloading scheme. The state probabilities of the different cooperating systems in the analytic model are determined by a fixed point iterative procedure. By investigating an inner and outer composite system we are able to analyze the system in imbalanced load conditions where the system reaches its full potential utilizing spare bandwidth. To evaluate the robustness of the system against users that try to exploit the system, the bandwidth received by prioritized users is quantified.
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Schwind, A., Seufert, M., Alay, Ö., Casas, P., Tran-Gia, P., Wamser, F.: Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed. IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17). , Dublin, Ireland (2017).
The MONROE testbed enables the objective performance assessment of MBB networks from the end-user perspective, using highly distributed measurements from fixed and mobile nodes. To quantify the performance of MBB networks for popular Internet services from a user-centric perspective, dedicated tools are needed. In this paper we extend the MONROE testbed to the Quality of Experience (QoE) domain, presenting the design and implementation of a QoE-capable measurement tool for YouTube video streaming. The measurement concept is based on emulating a virtual end-user device requesting video streams, which are then monitored at the network and application layers, on the basis of QoE-relevant features. The initial measurements conducted in the MONROE testbed and reported in this paper demonstrate the applicability of the implemented measurement concept.
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Wamser, F., Höfner, S., Seufert, M., Tran-Gia, P.: Server and Content Selection for MPEG DASH Video Streaming with Client Information. ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Los Angeles, CA, USA (2017).
In HTTP adaptive streaming (HAS), such as MPEG DASH, the video is split into chunks and is available in different quality levels. If the video chunks are stored or cached on different servers to deal with the high load in the network and the Quality of Experience (QoE) requirements of the users, the problem of content selection arises. In this paper, we evaluate client-side algorithms for dynamically selecting an appropriate content server during DASH video streaming. We present three algorithms with which the DASH client itself can determine the most appropriate server based on client-specific metrics, like actual latency or bandwidth to the content servers. We evaluate and discuss the proposed algorithms with respect to the resulting DASH streaming behavior in terms of buffer levels and quality level selection.
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Moldovan, C., Hagn, K., Sieber, C., Kellerer, W., Hoßfeld, T.: Keep Calm and Don’t Switch: About the Relationship Between Switches and Quality in HAS. 29th International Teletraffic Congress (ITC 29). p. 6. , Genoa, Italy (2017).
Video streaming has established itself as the main method to consume multimedia content on the Internet. The most widespread technique is HTTP Adaptive Streaming which is used by large video service platforms such as YouTube and Netflix. In order to guarantee a high QoE, different adaptation strategies have been developed that lead to different video playout patterns. While some strategies may be more aggressive than others and often adapt the video quality, it is not clear which strategy is the best. In this paper, we want to identify the trade-off between the av- erage video quality and switches in the quality during playout. We do this with a user-centric view and try to optimize the adaptation depending on the user preference with a quadratic program. This work allows us to put existing and future video adaptation algorithms in perspective with respect to user preferences. Our results show that the video quality can already be increased greatly by allowing few switches while more switches lead to diminishing gains. This is a novel discovery that is important for user-centric QoE-management which is of high interest for ISPs and video service providers.
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Surminski, S., Moldovan, C., Hoßfeld, T.: Saving Bandwidth by Limiting the Buffer Size in HTTP Adaptive Streaming. MMBnet 2017 Proceedings of the 9th GI/ITG Workshop. , Hamburg, Germany (2017).
Video streaming is one of the most bandwidth-intensive applications on the Internet. In HTTP adaptive video streaming the video quality is selected according to the available bandwidth. To compensate bandwidth fluctuations, players use a buffer in order to ensure a smooth video output. On one hand, if the buffer runs empty, the video playback stops, which users experience as negative. On the other hand, if the user aborts video playback, the video in the buffer was unnecessarily transmitted, hence this bandwidth was wasted. In this paper, we present a study in which we investigate the behavior of two video players and different buffer configurations in real-world bandwidth scenarios. Thereby, we focus on the dimensioning of the buffer size and the tradeoff between wasted bandwidth and the playback quality
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Zinner, T., Geissler, S., Helmschrott, F., Spinsante, S., Braeken, A.: An AAL-Oriented Measurement-based Evaluation of Different HTTP-based Data Transport Protocols. International Workshop on Protocols, Applications and Platforms for Enhanced Living Environments (2017).
A key requirement for Active and Assisted Living (AAL) environments is the exchange of data between different communication endpoints to support wide range of services and applications. Used communication protocols need to support the bidirectional flow of information and have to be optimized with regard to security or latency constraints. To address these issues, RESTful approaches have recently gained much attention from the community. In this context, different application layer transport protocols can be used to realize the required data exchange. Besides HTTP/1.1, developed and standardized in the 1990s, new protocols like HTTP/2 and the QUIC transfer protocol my be suitable candidates. The impact of the different protocols on the overall performance for web and AAL services is still an open research question. This paper narrows this gap by conducting a measurement-based comparison of the three described protocols with regard to their performance in terms of web page loading times for Google web services.
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Hoßfeld, T., Heegaard, P.E., Skorin-Kapov, L., Varela, M.: No Silver Bullet: QoE Metrics, QoE Fairness, and User Diversity in the Context of QoE Management. 9th International Conference on Quality of Multimedia Experience (QoMEX 2017). , Erfurt, Germany (2017).
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Borchert, K., Hirth, M., Zinner, T., Göritz, A.: Collecting Subjective Ratings in Enterprise Environments. 9th International Conference on Quality of Multimedia Experience (QoMEX). , Erfurt, Germany (2017).
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Seufert, M., Moldovan, C., Burger, V., Hoßfeld, T.: Applicability and Limitations of a Simple WiFi Hotspot Model for Cities. 13th International Conference on Network and Service Management (CNSM). , Tokio, Japan (2017).
Offloading mobile Internet data via WiFi has emerged as an omnipresent trend. WiFi networks are already widely deployed by many private and public institutions (e.g., libraries, cafes, restaurants) but also by commercial services to provide alternative Internet access for their customers and to mitigate the load on mobile networks. Moreover, smart cities start to install WiFi infrastructure for current and future civic services, e.g., based on sensor networks or the Internet of Things. A simple model for the distribution of WiFi hotspots in an urban environment is presented. The hotspot locations are modeled with a uniform distribution of the angle and an exponential distribution of the distance, which is truncated to the city limits. We compare the characteristics of this model in detail to the real distributions. Moreover, we show the applicability and the limitations of this model, and the results suggest that the model can be used in scenarios, which do not require an accurate spatial collocation of the hotspots, such as offloading potential, coverage, or signal strength.
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Loh, F., Burger, V., Wamser, F., Tran-Gia, P., Schembra, G., Rametta, C.: Performance Evaluation of Video Streaming Service Chains in Softwarized 5G Networks with Task Graph Reduction. 29th International Teletraffic Congress (ITC) (2017).
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Borchert, K., Hirth, M., Schnitzer, S., Rensing, C.: Impact of Task Recommendation Systems in Crowdsourcing Platforms. Workshop on Responsible Recommendation at RecSys 2017. , Como, Italy (2017).
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Seufert, M., Lange, S., Meixner, M.: Automated Decision Making based on Pareto Frontiers in the Context of Service Placement in Networks. 29th International Teletraffic Congress (ITC). , Genoa, Italy (2017).
Virtualization paradigms like cloud computing, software defined networking (SDN), and network functions virtualization (NFV) provide advantages with respect to aspects like flexibility, costs, and scalability. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services, such as virtual machines~(VMs), virtualized network functions~(VNFs), or SDN controllers, is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi-dimensional solutions. To this end, we investigate techniques from the domain of multi-attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making. In order to illustrate the functionality of the different scoring mechanisms, we perform a case study on a single network graph and a fixed number of objectives and service instances. Additionally, we present aggregated results from broad evaluations on the Internet Topology Zoo and a larger number of objectives as well as varying numbers of service instances. These allow making more reliable statements about the mechanisms' performance and agreement.
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Lange, S., Grigorjew, A., Zinner, T., Tran-Gia, P., Jarschel, M.: A Multi-Objective Heuristic for the Optimization of Virtual Network Function Chain Placement. 29th International Teletraffic Congress (ITC) (2017).
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Iffländer, L., Wamser, F., Metter, C., Tran-Gia, P., Kounev, S.: Performance Assessment of Cloud Migrations from Network and Application Point of View. Proceedings of 9th EAI International Conference on Mobile Networks and Management (MONAMI 2017). , Melbourne, Australia (2017).
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Borchert, K., Hirth, M., Zinner, T., Göritz, A.: Designing a Survey Tool for Monitoring Enterprise QoE. ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Los Angeles, CA, USA (2017).
Enterprise applications like SAP are part of the day-to-day work of a large number of employees. Similar to many modern applications, enterprise applications are often implemented in a distributed fashion and consequently suffer from network degradations resulting in impairments like increased loading delays. While the influence of these impairments on the perceived quality of users is well researched for consumer applications and network services, the impact of these impairments in a business environment is still unclear. To address this gap we develop a non-intrusive software tool for continuously collecting subjective ratings on the performance of an enterprise application from a large crowd of employees. Based on the feedback from a company and results from two initial field studies we discuss the specific challenges when assessing the perceived quality of employees during regular working hours and point our further research directions.
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Wamser, F., Seufert, M., Höfner, S., Tran-Gia, P.: Concept for Client-initiated Selection of Cloud Instances for Improving QoE of Distributed Cloud Services. ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). , Florianópolis, Brazil (2016).
We introduce a concept for client-initiated selection of service location and service quality for improving the Quality of Experience (QoE) of general cloud services. It is loosely based on the HTTP adaptive streaming approach (e.g., MPEG DASH). A manifest file compiled by the cloud service provider specifies the available service locations and qualities, from which the user selects the optimal service instance based on contextual information obtained from client measurements and user preferences. The proposed concept is defined and is implemented in two client-based decision algorithms for improving the QoE of a simple picture gallery cloud service. These decision algorithms are evaluated and their impact on the service delivery is discussed. The evaluation shows that it is possible to improve the service location and quality selection by light-weight client-based algorithms.
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Burger, V., Frances Pajo, J., Sanchez, O.R., Seufert, M., Schwartz, C., Wamser, F., Davoli, F., Tran-Gia, P.: Load Dynamics of a Multiplayer Online Battle Area and Simulative Assessment of Edge Server Placements. ACM Multimedia Systems Conference (MMSys). , Klagenfurt, Austria (2016).
Free-to-play models, streaming of games and eSports are reasons for online gaming to grow in popularity recently. On the forefront are multiplayer online battle arenas, which gain high popularity by introducing a competitive format that is easy to access and requires cooperation and team play. These games highly rely on fast reaction of the players, which makes latency the key performance indicator of such applications. To obtain low latency, this paper proposes moving game servers close to players towards the edge of the network. The performance of such mechanism highly depends on the geographic distribution of players. By analyzing match histories and statistics, we develop models for the arrival process and location of game requests. This allows us to evaluate the performance of edge server resource migration policies in an event based simulation. Our results show that a high number of edge servers is preferable compared to few larger edge servers to reduce the latency of players. This supports approaches that allow deploying virtual server instances in the back-haul.
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Hoßfeld, T., Skorin-Kapov, L., Heegaard, P.E., Varela, M., Chen, K.-T.: On Additive and Multiplicative QoS-QoE Models for Multiple QoS Parameters. 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS) (2016).
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Sieber, C., Heegaard, P.E., Hoßfeld, T., Kellerer, W.: Sacrificing efficiency for quality of experience: YouTube's redundant traffic behavior. IFIP Networking Conference (2016).
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Liotou, E., Hoßfeld, T., Moldovan, C., Metzger, F., Tsolkas, D., Passas, N.: Enriching HTTP adaptive streaming with context awareness: A tunnel case study. IEEE International Conference on Communications Workshops (ICC) (2016).
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Sackl, A., Schatz, R., Hoßfeld, T., Metzger, F., Lister, D., Irmer, R.: QoE Management made uneasy: The case of Cloud Gaming. IEEE Workshop on Quality of Experience-based Management for Future Internet Applications and Services (QoE-FI) (2016).
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Metzger, F., Rafetseder, A., Schwartz, C., Hoßfeld, T.: Games and frames: A strange tale of QoE studies. Eighth International Conference on Quality of Multimedia Experience (QoMEX) (2016).
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Moldovan, C., Sieber, C., Heegaard, P.E., Kellerer, W., Hoßfeld, T.: YouTube Can Do Better: Getting the Most Out of Video Adaptation. ITC and IEEE Workshop on QoE Centric Management (QCMan) (2016).
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Moldovan, C., Hoßfeld, T.: Impact of Variances on the QoE in Video Streaming. ITC and IEEE Workshop on QoE Centric Management (QCMan) (2016).
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Seufert, M., Lange, S., Meixner, M.: Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement. 1st International Workshop on Programmability for Cloud Networks and Applications (PROCON). , Würzburg, Germany (2016).
The network functions virtualization (NFV) paradigm provides advantages with respect to aspects like flexibility, costs, and scalability of networks. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services and virtualized network functions (VNFs) is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi dimensional solutions. To this end, we investigate techniques from the domain of multi attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making.
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Gebert, S., Geissler, S., Zinner, T., Nguyen-Ngoc, A., Lange, S., Tran-Gia, P.: ZOOM: Lightweight SDN-based Elephant Detection. First International Workshop on Programmability for Cloud Networks and Applications (PROCON). , Würzburg, Germany (2016).
Software Defined Networking (SDN) offers a holistic view of the network through a centralized control plane. Consequently, routing decisions can be made based on global knowledge about the network topology as well as its current state. As long living flows are suitable candidates for rerouting, their detection is crucial for efficient flow based traffic management. This work proposes the ZOOM algorithm for elephant detection in SDN networks. To this end, ZOOM follows a very lightweight approach that only uses packet counters implemented by OpenFlow switches and thus does not require any additional hardware. By exploiting this feature of OpenFlow switches, ZOOM allows lightweight and cost-effective elephant detection.
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Zinner, T., Hirth, M., Fischer, V., Hohlfeld, O.: ERWIN - Enabling the Reproducible Investigation of WaItiNg Times for Arbitrary Workflows. 8th International Conference on Quality of Multimedia Experiene (QoMEX). , Lisbon, Portugal (2016).
Delay effects can impact the Quality of Experience of interactive systems, which motivates research assessing delay impairments, mostly for web based systems. Current studies follow individual methodologies and typically assesses individual and custom-made web pages, whose construction requires expert knowledge in web technologies. A range of native, non-web applications cannot be easily modified for delay studies. Thus, a generalized methodology for assessing delay impacts for a broad range of applications that is assessable to researchers without (web) development expertise is still missing. This paper con- tributes to this open problem by i) presenting a new methodology for reproducible delay assessments in a broad class of (web-based) systems and ii) presenting an open-source implementation to be used by the community. This methodology particularly aims at making delay assessment available to a broad range of researchers by avoiding programming skills and thus by lowering the barrier for setting-up delay assessments.
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Seufert, M., Zach, O., Hoßfeld, T., Slanina, M., Tran-Gia, P.: Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality. 8th International Conference on Quality of Multimedia Experience (QoMEX). , Lisbon, Portugal (2016).
Adaptive crowdsourcing is a new approach to crowdsourced Quality of Experience (QoE) studies, which aims to improve the certainty of resulting QoE models by adaptively distributing a fixed budget of user ratings to the test conditions. The main idea of the adaptation is to dynamically allocate the next rating to a condition, for which the submitted ratings so far show a low certainty. This paper investigates the effects of statistical adaptation on the distribution of ratings and the goodness of the resulting QoE models. Thereby, it gives methodological advice how to select test conditions for future crowdsourced QoE studies.
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Gebert, S., Zinner, T., Lange, S., Schwartz, C., Tran-Gia, P.: Performance Modeling of Softwarized Network Functions Using Discrete-Time Analysis. 28th International Teletraffic Congress (ITC). , Würzburg, Germany (2016).
The softwarization of networks promises cost savings and better scalability of network functions by moving functionality from specialized devices into commercial off-the-shelf hardware. Generalized computing hardware offers many degrees for adjustment and tuning, which can affect performance and resource utilization. One of these adjustments are the interrupt mitigation techniques implemented by modern network interface cards and operating systems. Using these, an administrator can optimize either lower latencies or lower CPU overhead for processing of network traffic. In this work, an analytical model that allows computing relevant performance metrics like the packet processing time and the packet loss for generic virtualized network functions running on commodity hardware is developed. The applicability of the model is shown by comparing its outcome with measurements conducted in a local testbed. Based on this model, impact factors like the average packet interarrival time, the interarrival time distribution, and the duration of the interrupt aggregation interval are studied.
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Cofano, G., De Cicco, L., Zinner, T., Nguyen-Ngoc, A., Tran-Gia, P., Mascolo, S.: Design and Experimental Evaluation of Network-assisted Strategies for HTTP Adaptive Video Streaming. Best Student Paper Award, ACM Multimedia Systems Conference (MMSys). , Klagenfurt, Austria (2016).
In this paper we investigate several network-assisted streaming approaches which rely on active cooperation between video streaming applications and the network. We build a Video Control Plane which enforces Video Quality Fairness among concurrent video flows generated by heterogeneous client devices. To the purpose, a max-min fairness optimization problem is solved at run-time. We compare two approaches to actuate the optimal solution in an SDN network: the first one allocating network bandwidth slices to video flows, the second one guiding video players in the video bitrate selection. Performance is assessed through several QoE-related metrics, such as Video Quality Fairness, video quality, and switching frequency. The impact of client-side adaptation algorithms is also investigated.
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Moldovan, C., Metzger, F.: Bridging the Gap between QoE and User Engagement in HTTP Video Streaming. 28th International Teletraffic Congress (ITC 28) (2016).
On video streaming platforms, users expect a high Quality of Experience (QoE). In contrast, service and content providers aim at high User Engagement, most notably because their revenue is usually dependent on it. In order to satisfy users, it is critical to know how QoE is related to the User Engagement. However, no model for this relation exists yet. Current approaches to managing QoE are usually based on traffic analysis. However, this will become more difficult in the future since the encryption of Internet traffic progresses. In this paper, we present an approach to bringing QoE and User Engagement together with video streaming as the use case. We do this by fitting existing measurement data of User Engagement to obtain a model. Furthermore, we extend the existing queuing model for QoE and investigate the correlation between QoE and User Engagement in a simulation. Hereby, we model different scenarios where we quantify network bandwidth and video requirements. Our results show that there is a strong correlation between QoE and User Engagement. Additionally, we observe that simple buffer policies, which do not rely on buffer information, can still perform well. These revelations open the way for new approaches to QoE Management in the future Internet.
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Borchert, K., Hirth, M., Zinner, T., Mocanu, D.C.: Correlating QoE and Technical Parameters of an SAP System in an Enterprise Environment. QCMan IEEE Workshop on QoE centric Management (2016).
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Metzger, F., Rafetseder, A., Schwartz, C.: A Comprehensive End-to-End Lag Model for Online and Cloud Video Gaming. Proc. 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS 2016) (2016).
To further the knowledge of basic game mechanics and improve future video game Quality of Experience (QoE) studies we present a model and simulation for End-to-End (E2E) lag in networked and cloud computer games. E2E lag describes the latency between a user's action and the display of the action's results on the screen, thus providing both a basic measure for interactivity and a fundamental parameter to derived QoE metrics. In contrast to E2E lag models that focus on the network Round-Trip Time (RTT), the presented work also factors in the game's tickrate and framerate (and codec latencies in the case of cloud games). This reveals side effects that can entirely mask the network delay's contribution to the total lag, an important notion to consider for future game studies.
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Seufert, M., Hoßfeld, T., Schwind, A., Burger, V., Tran-Gia, P.: Group-based Communication in WhatsApp. 1st IFIP Internet of People Workshop (IoP). , Vienna, Austria (2016).
WhatsApp is a very popular mobile messaging application, which dominates today’s mobile communication. Especially the feature of group chats contributes to its success and changes the way people communicate. The group-based communication paradigm is investigated in this work, particularly focusing on the usage of WhatsApp, communication in group chats, and implications on mobile network traffic.
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Nguyen-Ngoc, A., Lange, S., Gebert, S., Zinner, T., Tran-Gia, P., Jarschel, M.: Performance Evaluation Mechanisms for FlowMod Message Processing in OpenFlow Switches. IEEE Sixth International Conference on Communications and Electronics. , Ha Long City, Vietnam (2016).
Network operators can benefit in terms of flexibility, cost, and vendor-independence when adopting the Software Defined Networking (SDN) paradigm. In many scenarios, the SDN controller orders the installation of new flow table entries in the switches it manages. Since such operations are handled in the slow path of the switches, the corresponding processing times constitute an important performance indicator for switches. This work focuses on a comparison of two mechanisms for evaluating the performance of OpenFlow switches with respect to the processing time of FlowMod messages. These mechanisms are characterized by different degrees of accuracy, cost, complexity, and the capability of performing measurements at run time. The first mechanism is based on the Spirent C1 dedicated testing platform, while the other uses a software module for the OpenDaylight controller. We assess their capabilities with respect to the abovementioned characteristics and quantify their accuracy by means of wiretaps that provide a ground truth regarding the measured processing times. By using three different switches in the experiments, it is possible to distinguish between hardware specific side-effects and general phenomena.
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Seufert, M., Hoßfeld, T.: One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing. 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS). , Berlin, Germany (2016).
Crowdsourcing studies for subjective quality testing have become a particularly useful tool for Quality of Experience researchers. Typically, crowdsouring studies are conducted by many unsupervised workers, which rate the perceived quality of several test conditions during one session (mixed within-subject test design). However, those studies often show to be very sensitive, for example, to test instructions, design, and filtering of unreliable participants. Moreover, the exposure of several test conditions to single workers potentially leads to an implicit training and anchoring of ratings. Therefore, this works investigates the extreme case of presenting only a single test condition to each worker (completely between-subjects test design). The results are compared to a typical crowdsourcing study design with multiple test conditions to discuss training effects in crowdsourcing studies. Thus, this work investigates if it is possible to use a simple ``one shot'' design with only one rating of a large number of workers instead of sophisticated (mixed or within-subject) test designs in crowdsourcing.
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Seufert, M., Casas, P., Wamser, F., Wehner, N., Schatz, R., Tran-Gia, P.: Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field. IEEE 6th International Conference on Communications and Electronics (ICCE). , Ha Long, Vietnam (2016).
YouTube video streaming is one of the most popular and most demanding services in cellular networks. Thus, operators are concerned about the quality of the streaming delivered by their networks and would like to monitor the Quality of Experience (QoE) of the end users. In this work, we conduct a field study of mobile YouTube video streaming, in which both network flow parameters and application-layer streaming parameters were monitored, and present the characteristics of current mobile YouTube streaming. The impact of both approaches is investigated showing that monitoring network parameters is not sufficient to directly infer the resulting QoE. In contrast, the streaming parameters, which can be obtained from application-layer monitoring, show high correlations to the subjectively experienced quality, and thus, are better suited for QoE monitoring.
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Dinh-Xuan, L., Seufert, M., Wamser, F., Tran-Gia, P.: QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service. IEEE 6th International Conference on Communications and Electronics (ICCE). , Ha Long, Vietnam (2016).
The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.
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Schwarzmann, S., Zinner, T., Dobrijevic, O.: Towards a Framework for Comparing QoE-Centric Mechanisms of Application-Network Interaction. Proceedings of the 4th International IEEE Workshop on Quality of Experience Centric Management (2016). , Würzburg (2016).
