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A New QoE-Driven Video Cache Management Scheme with Wireless Cloud Computing in Cellular Networks

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Abstract

With the development of wireless cloud computing, video caching in the radio access network (RAN) of cellular networks has attracted extensive attention due to its lower delay and higher resource utilization efficiency. Nevertheless, existing video cache management mostly made decisions only according to the video coding requirements, without considering users’ individual requirements for the video service and without making full use of the abundant network-side information in real time or from statistics. In this paper, we propose a new QoE (quality of experience)-driven video cache management scheme with the consideration of the parameters from three parties (i.e. client, base station, and RAN cache server) for video provisioning, with statistics of video popularities and under limited cache capacity. Specifically, through experiments we establish the mapping relationship between the QoE value and the three key parameters (i.e. the request rate from the client, the bandwidth of air interface, and the response rate of the cache server). Firstly, we allocate different gross caches for different video clips according to their popularities. Secondly, we optimize the cache space allocation for each individual video clip based on the QoE mapping relationship and the different models of the request rate and the bandwidth, with the convex optimization method and the Lagrange multiplier solution. The experiments results indicate that the proposed video cache scheme has better QoE performance under the constraints of the total cache capacity, specific distributions of the request rate and the bandwidth.

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References

  1. Cisco report (2014) Cisco visual networking index: global mobile data traffic forecast update, 2013–2018, http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white_paper_c11-520862.html, July 20, 2014

  2. Oyman O, Singh S (2012) Quality of experience for HTTP adaptive streaming services. IEEE Commun Mag 50(4):20–27

    Article  Google Scholar 

  3. Borst S, Gupt V, Walid A (2010) Distributed caching algorithms for content distribution networks. In: Proceedings of IEEE INFOCOM, pp 1–9

  4. Miao Z, Ortega A (2002) Scalable proxy caching of video under storage constraints. IEEE J Sel Areas Commun 20(7):1315–1327

    Article  Google Scholar 

  5. Ma W, Du DHC (2004) Design a progressive video caching policy for video proxy servers. IEEE Trans Multimedia 6(4):599–610

    Article  Google Scholar 

  6. Ahlehagh H, Dey S (2013) Adaptive bit rate capable video caching and scheduling. In: Proceedings of IEEE Wireless Communications and Networking Conference, pp 1357–1362

  7. Ahlehagh H, Dey S (2014) Video-aware scheduling and caching in the radio access network. IEEE/ACM Trans Networking 22(5):1444–1462

    Article  Google Scholar 

  8. Chien Y L, Lin K C J, Chen M S (2015) Machine learning based rate adaptation with elastic feature selection for HTTP-based streaming. In: Proceedings of IEEE International Conference on Multimedia and Expo, pp 1–6

  9. Joseph V, Veciana G (2014) NOVA: QoE-driven optimization of DASH-based video delivery in networks. In: Proceedings of IEEE INFOCOM, pp 82–90

  10. Chen M, Zhang Y, Hu L, Taleb T et al (2015) Cloud-based wireless network: virtualized, reconfigurable, smart wireless network to enable 5G technologies. Mob Netw Appl. doi:10.1007/s11036-015-0590-7

    Google Scholar 

  11. Zhang W, Wen Y, Chen Z et al (2013) QoE-driven cache management for HTTP adaptive bit rate streaming over wireless networks. IEEE Trans Multimedia 15(6):1431–1445

    Article  Google Scholar 

  12. Hofmann I, Farber N, Fuchs H (2011) A study of network performance with application to adaptive HTTP streaming. In: Proceedings of IEEE Int Symp Broadband Multimedia Systems and Broadcasting, pp 1–6

  13. Liu C, Bouazizi I, and Gabbouj M (2011) Rate adaptation for adaptive HTTP streaming. In: Proceedings of ACM Conf Multimedia Systems, pp 169–174

  14. Adzic V, Kalva H, Furht B (2011) Optimized adaptive HTTP streaming for mobile devices. Proc SPIE 8135(1):81350T-81350T-10

    Google Scholar 

  15. Reis A B, Chakareski J, Kassler A, Sargento S (2010) Distortion optimized multi-service scheduling for next-generation wireless mesh networks. In: Proceedings of INFOCOM IEEE Conf Computer Communications Workshops, pp 1–6

  16. Thakolsri S, Kellerer W, Steinbach E (2010) QoE-based rate adaptation scheme selection for resource-constrained wireless video transmission. In: Proceedings of International Conference on Multimedia, pp 783–786

  17. Wang B, Sen S, Adler M, et al. (2002) Optimal proxy cache allocation for efficient streaming media distribution. In: Proceedings of IEEE INFOCOM: 1726–1735

  18. Verscheure O, Venkatramani C, Frossard P et al (2001) Joint server scheduling and proxy caching for video delivery. Comput Commun 25(4):413–423

    Article  Google Scholar 

  19. Liu J, Li B (2004) Qos-based joint scheduling and caching algorithm for multimedia objects. World Wide Web 7(3):281–296

    Article  Google Scholar 

  20. Shen S H, Akella A (2013) An information-aware QoE-centric mobile video cache. In: Proceedings of International Conference on Mobile Computing & Networking, pp 401–412

  21. Essaili AEI, Schroeder D, Steinbach E et al (2014) QoE-based traffic and resource management for adaptive HTTP video delivery in LTE. IEEE Trans Circuits Syst Video Technol 25(6):988–1001

    Article  Google Scholar 

  22. Su G M, Su X, Bai Y, Wang M, et al. (2015) QoE in video streaming over wireless networks: perspectives and research challenges. Wirel Netw (2015):1–23. doi:10.1007/s11276-015-1028-7

  23. Wang YM, Sun MY, Wang KY, Zhang L (2015) QoE estimation with layered mapping for HTTP video streaming over wireless networks. Int J Commun Syst. doi:10.1002/dac.2911

    Google Scholar 

  24. Nocedal J, Wright SJ (1999) Numerical optimization. Operations Research, Springer, New York

    Book  MATH  Google Scholar 

  25. ITU-R Rec. BT.500 -11 (2002) Methodology for the subjective assessment of the quality of televisions pictures

  26. ITU-R Rec. P.910 (1999) Subjective video quality assessment methods for multimedia applications

Download references

Acknowledgments

The authors would like to thank the editor in chief and the anonymous reviewers for their helpful comments and suggestions. This work is partially supported by the Fundamental Research Funds for the Central Universities under grant No. 2014ZD03-02, the 111 Project (No. B08004) and the Major projects of national science and technology (2015ZX03001030).

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Authors and Affiliations

  1. Key Lab of Universal Wireless Communication, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Yumei Wang, Xiaojiang Zhou, Mengyao Sun, Lin Zhang & Xiaofei Wu

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  1. Yumei Wang
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  2. Xiaojiang Zhou
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  3. Mengyao Sun
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  4. Lin Zhang
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  5. Xiaofei Wu
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Correspondence to Yumei Wang.

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Wang, Y., Zhou, X., Sun, M. et al. A New QoE-Driven Video Cache Management Scheme with Wireless Cloud Computing in Cellular Networks. Mobile Netw Appl 22, 72–82 (2017). https://doi.org/10.1007/s11036-016-0689-5

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