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Data-Driven QoE Measurement

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Encyclopedia of Wireless Networks

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Synonyms

Data-access QoE management; Data-aware QoE management; Data-driven QoE analysis; Data-driven QoE assessment; Data-driven QoE improvement; Data-driven QoE management; Data-driven QoE optimization; Data-driven QoE prediction; Data-driven QoE visualization; Data-oriented QoE management

Definition

Recently, the strict definition of data-driven QoE measurement has not been given. The International Telecommunication Union (ITU-T) has defined the QoE concept as the entire thing of availability of services subjectively perceived by end users. The definition of QoE by the European Qualinet is the degree of satisfaction or annoyance of the end users of services because the utility and/or the expectations regarding services are based on end-user attitudes and current service situations (He et al., 2018). Furthermore, data-driven QoE measurement can be defined from the perspective of objective-based or subjective-based metrics. Generally speaking, data-driven QoE measurement is the...

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References

  • Canbaz M, Thom J, Gunes MH (2017) Comparative analysis of internet topology data sets. In: Proceedings of 2017 IEEE conference on computer communications workshops (INFOCOM WKSHPS)

    Google Scholar 

  • Chen K, Shen H (2015) Maximizing P2P file access availability in mobile ad hoc networks though replication for efficient file sharing. IEEE Trans Comput 64(4):1029–1042

    Article  MathSciNet  Google Scholar 

  • Du M, Wang K, Xia Z, Zhang Y (2018) Differential privacy preserving of training model in wireless big data with edge computing. IEEE Trans Big Data. https://doi.org/10.1109/TBDATA.2018.2829886

  • Fang Q, Wang J, Gong Q (2016) QoS-driven power management of data centers via model predictive control. IEEE Trans Auto Sci Eng 13(4):1557–1566

    Article  Google Scholar 

  • He X, Wang K, Huang H, Miyazaki T, Wang Y, Guo S (2018) Green resource allocation based on deep reinforcement learning in content-centric IoT. IEEE Trans Emerg Top Comput. https://doi.org/10.1109/TETC.2018.2805718

  • He X, Wang K, Huang H, Miyazaki T, Wang Y, Sun Y (2018) QoE-driven joint resource allocation for content delivery in fog computing environment. In Proceedings of ICC.

    Google Scholar 

  • Jiang J, Sekar V, Milner H, Shepherd D, Stoica I, Zhang H (2016a) CFA: a practical prediction system for video QoE optimization. In: Proceedings of 13th USENIX symposium on networked systems design and implementation (NSDI’16)

    Google Scholar 

  • Jiang J, Sun S, Sekar V, Zhang H (2017) Pytheas: enabling data-driven quality of experience optimization using group-based exploration-exploitation. In: Proceedings of 14th USENIX symposium on networked systems design and implementation (NSDI’17)

    Google Scholar 

  • Purohit L, Kumar S (2018) A classification based web service selection approach. IEEE Trans Serv Comput. https://doi.org/10.1109/TSC.2018.2805352

  • Sterca A, Hellwagner H, Florian Boian F, Vancea A (2016) Media-friendly and TCP-friendly rate control protocols for multimedia streaming. IEEE Trans Circ Syst Video Technol 26(8):1516–1531

    Article  Google Scholar 

  • Usman M, Yang N, Jan M, He X, Xu M, Lam k (2018) A joint framework for QoS and QoE for video transmission over wireless multimedia sensor networks. IEEE Trans Mob Comput 17(4):746–759

    Google Scholar 

  • Wang K, Gao H, Xu X, Jiang J, Yue D (2016) An energy-efficient reliable data transmission scheme for complex environmental monitoring in underwater acoustic sensor networks. IEEE Sens J 16(11):4051–4062

    Article  Google Scholar 

  • Wang K, Mi J, Xu C, Zhu Q, Shu L, Deng DJ (2016) Real-time load reduction in multimedia big data for mobile Internet. ACM Trans Mult Comput Commun App 12(5):76

    Google Scholar 

  • Wang K, Zhuo L, Shao Y, Yue D, Tsang KF (2016) Towards distributed data processing on intelligent leakpoints prediction in petrochemical industries. IEEE Trans Ind Informatics 12(6):2091–2102

    Article  Google Scholar 

  • Wang Y, He D, Ding L, Zhang W, Li W, Wu Y, Liu N, Wang Y (2017b) Media transmission by cooperation of cellular network and broadcasting network. IEEE Trans Broad 63(3):571–576

    Article  Google Scholar 

  • Wang K, Zhou Q, Guo S, Luo J (2018) Cluster frameworks for efficient scheduling and resource allocation in data center networks: a survey. IEEE Commun Surv Tutor 20(4):3560–3580

    Article  Google Scholar 

  • Wang Y, Wang* K, Huang H, Miyazaki T, Guo S (2019) Traffic and computation co-offloading with reinforcement learning in fog computing for industrial applications. IEEE Transactions on Industrial Informatics. IEEE Trans Ind Informatics 15(2):976–986

    Google Scholar 

  • Xu C, Wang K, Li L, Xia R, Guo S, Guo M (2018) Renewable energy-aware big data analytics in geo-distributed data centers with reinforcement learning. IEEE Trans Netw Sci Eng. https://doi.org/10.1109/TNSE.2018.2813333

  • Zhang J, Wang Z, Wang K, Guo S, Guo M (2017) Improving power efficiency for online video streaming service: a self-adaptive approach. IEEE Trans Sust Comput. https://doi.org/10.1109/TSUSC.2017.2739798

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Author information

Authors and Affiliations

  1. College of IoT, Nanjing University of Posts and Telecommunications, Nanjing, China

    Xiaoming He

  2. Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, USA

    Kun Wang

Authors
  1. Xiaoming He
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  2. Kun Wang
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo , Waterloo, ON, Canada

    Xuemin (Sherman) Shen

  2. Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON, Canada

    Xiaodong Lin

  3. Dpt.of Electrical & Computer Engineering, University of Nebraska–Lincoln, Omaha, NE, USA

    Kuan Zhang

Section Editor information

  1. Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Song Guo

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He, X., Wang, K. (2019). Data-Driven QoE Measurement. In: Shen, X., Lin, X., Zhang, K. (eds) Encyclopedia of Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-32903-1_89-1

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  • DOI: https://doi.org/10.1007/978-3-319-32903-1_89-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32903-1

  • Online ISBN: 978-3-319-32903-1

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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