2016

• Antons, J.-N., Egger, S., Hoßfeld, T., Möller, S.: Proceedings of The Fifth Workshop on Perceptual Quality of Systems (PQS).ISCA, TU Berlin, Germany (2016).
  [ BibTeX ][ EndNote ]
   
  @book{info3-book-2016-3, address = {TU Berlin, Germany}, author = {Antons, Jan-Niklas and Egger, Sebastian and Hoßfeld, Tobias and Möller, Sebastian}, keywords = {myown sys:hidden:book}, month = 8, publisher = {ISCA}, title = {Proceedings of The Fifth Workshop on Perceptual Quality of Systems (PQS)}, year = 2016 }
  %0 Book %1 info3-book-2016-3 %A Antons, Jan-Niklas %A Egger, Sebastian %A Hoßfeld, Tobias %A Möller, Sebastian %C TU Berlin, Germany %D 2016 %I ISCA %T Proceedings of The Fifth Workshop on Perceptual Quality of Systems (PQS)
• Hoßfeld, T., Chan, G., Mark, B.L., Timm-Giel, A.: Proceedings of The 28th International Teletraffic Congress 2016 (ITC 28).ITC, IEEE, ACM, Würzburg, Germany (2016).
  [ BibTeX ][ EndNote ]
   
  @book{info3-book-2016-2, address = {Würzburg, Germany}, author = {Hoßfeld, Tobias and Chan, Gary and Mark, Brian L. and Timm-Giel, Andreas}, keywords = {myown sys:hidden:book}, month = 9, publisher = {ITC, IEEE, ACM}, title = {Proceedings of The 28th International Teletraffic Congress 2016 (ITC 28)}, year = 2016 }
  %0 Book %1 info3-book-2016-2 %A Hoßfeld, Tobias %A Chan, Gary %A Mark, Brian L. %A Timm-Giel, Andreas %C Würzburg, Germany %D 2016 %I ITC, IEEE, ACM %T Proceedings of The 28th International Teletraffic Congress 2016 (ITC 28)
• Agüero, R., Zinner, T., García-Lozano, M., Wenning, B.-L., Timm-Giel, A.: Mobile Networks and Management.Springer, Santander, Spain (2016).
  [ BibTeX ][ EndNote ]
   
  @book{info3-book-2016-1, address = {Santander, Spain}, author = {Agüero, Ramón and Zinner, Thomas and García-Lozano, Mario and Wenning, Bernd-Ludwig and Timm-Giel, Andreas}, booktitle = {6th International Conference (MONAMI 2014), September 22-26, 2014, Revised Selected Papers}, keywords = {myown sys:hidden:book}, publisher = {Springer}, title = {Mobile Networks and Management}, year = 2016 }
  %0 Book %1 info3-book-2016-1 %A Agüero, Ramón %A Zinner, Thomas %A García-Lozano, Mario %A Wenning, Bernd-Ludwig %A Timm-Giel, Andreas %B 6th International Conference (MONAMI 2014), September 22-26, 2014, Revised Selected Papers %C Santander, Spain %D 2016 %I Springer %T Mobile Networks and Management

2018

• Schwarzmann, S., Blenk, A., Dobrijevic, O., Jarschel, M., Hotho, A., Zinner, T., Wamser, F.: Big-Data Helps SDN to Improve Application Specific Quality of Service.Big Data and Software Defined Networks. IET (2018).
  [ Abstract ][ BibTeX ][ EndNote ]
   
  This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.
  @incollection{info3-incollection-2018-2, abstract = {This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.}, author = {Schwarzmann, Susanna and Blenk, Andreas and Dobrijevic, Ognjen and Jarschel, Michael and Hotho, Andreas and Zinner, Thomas and Wamser, Florian}, booktitle = {Big Data and Software Defined Networks}, keywords = {sys:hidden:incollection myown ngn}, publisher = {IET}, title = {Big-Data Helps SDN to Improve Application Specific Quality of Service}, year = 2018 }
  %0 Book Section %1 info3-incollection-2018-2 %A Schwarzmann, Susanna %A Blenk, Andreas %A Dobrijevic, Ognjen %A Jarschel, Michael %A Hotho, Andreas %A Zinner, Thomas %A Wamser, Florian %B Big Data and Software Defined Networks %D 2018 %I IET %T Big-Data Helps SDN to Improve Application Specific Quality of Service %X This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.
• Metzger, F., Hoßfeld, T., Skorin-Kapov, L., Liotou, E., Pocta, P., Melvin, H., Siris, V., Zgank, A., Jarschel, M.: Context Monitoring for Improved System Performance and QoE. In: Ganchev, I., van der Mei, R.D., and van den Berg, H. (eds.) Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools. Springer International Publishing (2018).
  [ Abstract ][ BibTeX ][ EndNote ]
   
  Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational. The benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming. Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.
  @incollection{info3-incollection-2018-3, abstract = {Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational. The benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming. Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.}, author = {Metzger, Florian and Hoßfeld, Tobias and Skorin-Kapov, Lea and Liotou, Eirini and Pocta, Peter and Melvin, Hugh and Siris, Vasilios and Zgank, Andrej and Jarschel, Michael}, booktitle = {Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools}, editor = {Ganchev, Ivan and van der Mei, R. D. and van den Berg, Hans}, keywords = {sys:hidden:incollection myown}, month = 5, publisher = {Springer International Publishing}, title = {Context Monitoring for Improved System Performance and QoE}, year = 2018 }
  %0 Book Section %1 info3-incollection-2018-3 %A Metzger, Florian %A Hoßfeld, Tobias %A Skorin-Kapov, Lea %A Liotou, Eirini %A Pocta, Peter %A Melvin, Hugh %A Siris, Vasilios %A Zgank, Andrej %A Jarschel, Michael %B Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools %D 2018 %E Ganchev, Ivan %E van der Mei, R. D. %E van den Berg, Hans %I Springer International Publishing %T Context Monitoring for Improved System Performance and QoE %X Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational. The benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming. Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.
• Liotou, E., Hoßfeld, T., Moldovan, C., Metzger, F., Tsolkas, D., Passas, N.: The Value of Context-Awareness in Bandwidth-Challenging HTTP Adaptive Streaming Scenarios. In: Ganchev, I., van der Mei, R.D., and van den Berg, H. (eds.) Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools. Springer International Publishing (2018).
  [ Abstract ][ BibTeX ][ EndNote ]
   
  Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.
  @incollection{info3-incollection-2018-4, abstract = {Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.}, author = {Liotou, Eirini and Hoßfeld, Tobias and Moldovan, Christian and Metzger, Florian and Tsolkas, Dimitris and Passas, Nikos}, booktitle = {Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools}, editor = {Ganchev, Ivan and van der Mei, R. D. and van den Berg, Hans}, keywords = {sys:hidden:incollection myown fullstack}, month = 5, publisher = {Springer International Publishing}, title = {The Value of Context-Awareness in Bandwidth-Challenging HTTP Adaptive Streaming Scenarios}, year = 2018 }
  %0 Book Section %1 info3-incollection-2018-4 %A Liotou, Eirini %A Hoßfeld, Tobias %A Moldovan, Christian %A Metzger, Florian %A Tsolkas, Dimitris %A Passas, Nikos %B Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools %D 2018 %E Ganchev, Ivan %E van der Mei, R. D. %E van den Berg, Hans %I Springer International Publishing %T The Value of Context-Awareness in Bandwidth-Challenging HTTP Adaptive Streaming Scenarios %X Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.

2019

• Metzger, F., Hoßfeld, T., Bauer, A., Kounev, S., Heegaard, P.E.: Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud.Proceedings of the IEEE.107,679-694 (2019).
  [ Abstract ][ BibTeX ][ EndNote ] [ Download ]
   
  As the Internet of Things (IoT) continues to gain traction in telecommunication networks, a very large number of devices are expected to be connected and used in the near future. In order to appropriately plan and dimension the network, as well as the back-end cloud systems and the resulting signaling load, traffic models are employed. These models are designed to accurately capture and predict the properties of IoT traffic in a concise manner. To achieve this, Poisson process approximations, based on the Palm–Khintchine theorem, have often been used in the past. Due to the scale (and the difference in scales in various IoT networks) of the modeled systems, the fidelity of this approximation is crucial, as, in practice, it is very challenging to accurately measure or simulate large-scale IoT deployments. The main goal of this paper is to understand the level of accuracy of the Poisson approximation model. To this end, we first survey both common IoT network properties and network scales as well as traffic types. Second, we explain and discuss the Palm–Khintiche theorem, how it is applied to the problem, and which inaccuracies can occur when using it. Based on this, we derive guidelines as to when a Poisson process can be assumed for aggregated periodic IoT traffic. Finally, we evaluate our approach in the context of an IoT cloud scaler use case.
  @article{info3-article-2019-3, abstract = {As the Internet of Things (IoT) continues to gain traction in telecommunication networks, a very large number of devices are expected to be connected and used in the near future. In order to appropriately plan and dimension the network, as well as the back-end cloud systems and the resulting signaling load, traffic models are employed. These models are designed to accurately capture and predict the properties of IoT traffic in a concise manner. To achieve this, Poisson process approximations, based on the Palm–Khintchine theorem, have often been used in the past. Due to the scale (and the difference in scales in various IoT networks) of the modeled systems, the fidelity of this approximation is crucial, as, in practice, it is very challenging to accurately measure or simulate large-scale IoT deployments. The main goal of this paper is to understand the level of accuracy of the Poisson approximation model. To this end, we first survey both common IoT network properties and network scales as well as traffic types. Second, we explain and discuss the Palm–Khintiche theorem, how it is applied to the problem, and which inaccuracies can occur when using it. Based on this, we derive guidelines as to when a Poisson process can be assumed for aggregated periodic IoT traffic. Finally, we evaluate our approach in the context of an IoT cloud scaler use case.}, author = {Metzger, Florian and Hoßfeld, Tobias and Bauer, André and Kounev, Samuel and Heegaard, Poul E.}, journal = {Proceedings of the IEEE}, keywords = {myown fullstack iot sys:hidden:article doi:10.1109/JPROC.2019.2901578}, month = 4, number = 4, pages = {679-694}, title = {Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud}, volume = 107, year = 2019 }
  %0 Journal Article %1 info3-article-2019-3 %A Metzger, Florian %A Hoßfeld, Tobias %A Bauer, André %A Kounev, Samuel %A Heegaard, Poul E. %D 2019 %J Proceedings of the IEEE %N 4 %P 679-694 %T Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud %V 107 %X As the Internet of Things (IoT) continues to gain traction in telecommunication networks, a very large number of devices are expected to be connected and used in the near future. In order to appropriately plan and dimension the network, as well as the back-end cloud systems and the resulting signaling load, traffic models are employed. These models are designed to accurately capture and predict the properties of IoT traffic in a concise manner. To achieve this, Poisson process approximations, based on the Palm–Khintchine theorem, have often been used in the past. Due to the scale (and the difference in scales in various IoT networks) of the modeled systems, the fidelity of this approximation is crucial, as, in practice, it is very challenging to accurately measure or simulate large-scale IoT deployments. The main goal of this paper is to understand the level of accuracy of the Poisson approximation model. To this end, we first survey both common IoT network properties and network scales as well as traffic types. Second, we explain and discuss the Palm–Khintiche theorem, how it is applied to the problem, and which inaccuracies can occur when using it. Based on this, we derive guidelines as to when a Poisson process can be assumed for aggregated periodic IoT traffic. Finally, we evaluate our approach in the context of an IoT cloud scaler use case.

2018

• Hoßfeld, T., Timmerer, C.: Quality of experience column: an introduction.ACM SIGMultimedia Records.10 (2018).
  [ BibTeX ][ EndNote ]
   
  @article{info3-article-2018-9, author = {Hoßfeld, Tobias and Timmerer, Christian}, journal = {ACM SIGMultimedia Records}, keywords = {myown sys:hidden:article}, number = 3, pages = 10, title = {Quality of experience column: an introduction}, year = 2018 }
  %0 Journal Article %1 info3-article-2018-9 %A Hoßfeld, Tobias %A Timmerer, Christian %D 2018 %J ACM SIGMultimedia Records %N 3 %P 10 %T Quality of experience column: an introduction
• Sieber, C., Hagn, K., Moldovan, C., Hoßfeld, T., Kellerer, W.: Towards Machine Learning-Based Optimal HAS.arXiv preprint arXiv:1808.08065. (2018).
  [ BibTeX ][ EndNote ]
   
  @article{info3-article-2018-8, author = {Sieber, Christian and Hagn, Korbinian and Moldovan, Christian and Hoßfeld, Tobias and Kellerer, Wolfgang}, journal = {arXiv preprint arXiv:1808.08065}, keywords = {myown sys:hidden:article}, title = {Towards Machine Learning-Based Optimal HAS}, year = 2018 }
  %0 Journal Article %1 info3-article-2018-8 %A Sieber, Christian %A Hagn, Korbinian %A Moldovan, Christian %A Hoßfeld, Tobias %A Kellerer, Wolfgang %D 2018 %J arXiv preprint arXiv:1808.08065 %T Towards Machine Learning-Based Optimal HAS

2019

• 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).
  [ Abstract ][ BibTeX ][ EndNote ] [ Download ]
   
  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.
  @inproceedings{info3-inproceedings-2019-21, abstract = {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.}, author = {Moldovan, Christian and Wamser, Florian and Hoßfeld, Tobias}, booktitle = {2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {myown sys:hidden:inproceedings dfg-sdn can}, month = 6, title = {User Behavior and Engagement of a Mobile Video Streaming User from Crowdsourced Measurements}, year = 2019 }
  %0 Conference Paper %1 info3-inproceedings-2019-21 %A Moldovan, Christian %A Wamser, Florian %A Hoßfeld, Tobias %B 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX) %D 2019 %T User Behavior and Engagement of a Mobile Video Streaming User from Crowdsourced Measurements %X 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.
• 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).
  [ Abstract ][ BibTeX ][ EndNote ] [ Download ]
   
  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.
  @inproceedings{info3-inproceedings-2019-19, abstract = {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.}, author = {Geißler, Stefan and Prantl, Thomas and Lange, Stanislav and Wamser, Florian and Hoßfeld, Tobias}, booktitle = {31st International Teletraffic Congress (ITC). , Budapest, Hungary}, keywords = {myown blockchain sys:hidden:inproceedings ngn net-op}, month = 8, title = {Discrete-Time Analysis of the Blockchain Distributed Ledger Technology}, year = 2019 }
  %0 Conference Paper %1 info3-inproceedings-2019-19 %A Geißler, Stefan %A Prantl, Thomas %A Lange, Stanislav %A Wamser, Florian %A Hoßfeld, Tobias %B 31st International Teletraffic Congress (ITC). , Budapest, Hungary %D 2019 %T Discrete-Time Analysis of the Blockchain Distributed Ledger Technology %X 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.

2018

• 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).
  [ BibTeX ][ EndNote ]
   
  @inproceedings{info3-inproceedings-2018-49, author = {Grigorjew, Alexej and Gray, Nicholas and Hoßfeld, Tobias and Shukla, Apoorv and Zinner, Thomas}, booktitle = {Student Workshop of the 14th International Conference on emerging Networking EXperiments and Technologies}, keywords = {myown sys:hidden:inproceedings ngn tech-net}, month = 12, title = {Bridging the Gap Between Programming and Implementation of Networking Devices}, year = 2018 }
  %0 Conference Paper %1 info3-inproceedings-2018-49 %A Grigorjew, Alexej %A Gray, Nicholas %A Hoßfeld, Tobias %A Shukla, Apoorv %A Zinner, Thomas %B Student Workshop of the 14th International Conference on emerging Networking EXperiments and Technologies %D 2018 %T Bridging the Gap Between Programming and Implementation of Networking Devices

2016

• Gebert, S., Zinner, T., Lange, S., Schwartz, C., Tran-Gia, P.: Discrete-Time Analysis: Deriving the Distribution of the Number of Events in an Arbitrarily Distributed Interval.University of Wuerzburg (2016).
  [ BibTeX ][ EndNote ] [ Download ]
   
  @techreport{info3-techreport-2016-1, author = {Gebert, Steffen and Zinner, Thomas and Lange, Stanislav and Schwartz, Christian and Tran-Gia, Phuoc}, institution = {University of Wuerzburg}, keywords = {myown sys:hidden:techreport}, month = 6, number = 498, title = {Discrete-Time Analysis: Deriving the Distribution of the Number of Events in an Arbitrarily Distributed Interval}, year = 2016 }
  %0 Report %1 info3-techreport-2016-1 %A Gebert, Steffen %A Zinner, Thomas %A Lange, Stanislav %A Schwartz, Christian %A Tran-Gia, Phuoc %D 2016 %N 498 %T Discrete-Time Analysis: Deriving the Distribution of the Number of Events in an Arbitrarily Distributed Interval

2015

• Seufert, M., Hoßfeld, T., Sperb Machado, G., Bocek, T., Biancani, M., Cruschelli, P., Lapacz, R., Darzanos, G., Papafili, I., Wajda, K.: A Survey of Cloud Services and Potential Applications of Social Awareness.University of Wuerzburg (2015).
  [ BibTeX ][ EndNote ]
   
  @techreport{info3-techreport-2015-3, author = {Seufert, Michael and Hoßfeld, Tobias and Sperb Machado, Guilherme and Bocek, Thomas and Biancani, Matteo and Cruschelli, Paolo and Lapacz, Roman and Darzanos, George and Papafili, Ioanna and Wajda, Krzysztof}, institution = {University of Wuerzburg}, keywords = {myown sys:hidden:techreport smartenit can}, month = 11, number = 496, title = {A Survey of Cloud Services and Potential Applications of Social Awareness}, year = 2015 }
  %0 Report %1 info3-techreport-2015-3 %A Seufert, Michael %A Hoßfeld, Tobias %A Sperb Machado, Guilherme %A Bocek, Thomas %A Biancani, Matteo %A Cruschelli, Paolo %A Lapacz, Roman %A Darzanos, George %A Papafili, Ioanna %A Wajda, Krzysztof %D 2015 %N 496 %T A Survey of Cloud Services and Potential Applications of Social Awareness

2013

• Schwartz, C., Hoßfeld, T., Lehrieder, F., Tran-Gia, P.: Performance Analysis of the Trade-off Between Signalling Load and Power Consumption for Popular Smartphone Apps in 3G Networks.University of Wuerzburg (2013).
  [ BibTeX ][ EndNote ] [ Download ]
   
  @techreport{info3-techreport-2013-260, author = {Schwartz, Christian and Hoßfeld, Tobias and Lehrieder, Frank and Tran-Gia, Phuoc}, institution = {University of Wuerzburg}, keywords = {myown sys:hidden:techreport}, month = 1, number = 485, title = {Performance Analysis of the Trade-off Between Signalling Load and Power Consumption for Popular Smartphone Apps in 3G Networks}, year = 2013 }
  %0 Report %1 info3-techreport-2013-260 %A Schwartz, Christian %A Hoßfeld, Tobias %A Lehrieder, Frank %A Tran-Gia, Phuoc %D 2013 %N 485 %T Performance Analysis of the Trade-off Between Signalling Load and Power Consumption for Popular Smartphone Apps in 3G Networks