Video streaming distribution over mobile Internet: a survey

Mu WANG, Changqiao XU, Shijie JIA, Gabriel-Miro MUNTEAN

PDF(1689 KB)
PDF(1689 KB)
Front. Comput. Sci. ›› 2018, Vol. 12 ›› Issue (6) : 1039-1059. DOI: 10.1007/s11704-018-7153-6
REVIEW ARTICLE

Video streaming distribution over mobile Internet: a survey

Author information +
History +

Abstract

In recent times, mobile Internet has witnessed the explosive growth of video applications, embracing user-generated content, Internet Protocol television (IPTV), live streaming, video-on-demand, video conferencing, and FaceTime-like video communications. The exponential rise of video traffic and dynamic user behaviors have proved to be a major challenge to video resource sharing and delivery in the mobile environment. In this article, we present a survey of state-of-the-art video distribution solutions over the Internet. We first discuss the challenges of mobile peer-to-peer (MP2P)-based solutions and categorize them into two groups. We discuss the design idea, characteristics, and drawbacks of solutions in each group.We also give a reviewfor solutions of video transmission in wireless heterogeneous networks. Furthermore, we summarize the information-centric networking (ICN)-based video solutions in terms of in-network caching and name-based routing. Finally, we outline the open issues for mobile video systems that require further studies.

Keywords

video streaming / content distribution / resource management / mobile Internet

Cite this article

Download citation ▾
Mu WANG, Changqiao XU, Shijie JIA, Gabriel-Miro MUNTEAN. Video streaming distribution over mobile Internet: a survey. Front. Comput. Sci., 2018, 12(6): 1039‒1059 https://doi.org/10.1007/s11704-018-7153-6

References

[1]
Bae S H, Kim J, Kim M, Cho S, Choi J S. Assessments of subjective video quality on HEVC-encoded 4K-UHD video for beyond- HDTV broadcasting services. IEEE Transactions on Broadcasting, 2013, 59(2): 209–222
CrossRef Google scholar
[2]
Roy S D, Lotan G, Zeng W. Social multimedia signals: sense, process, and put them to work. IEEE Multimedia, 2013, 20(1): 7–13
CrossRef Google scholar
[3]
Abeydeera M, Karunaratne M, Karunaratne G, Silva K D, Pasqual A. 4K real-time HEVC decoder on an FPGA. IEEE Transactions on Circuits and Systems for Video Technology, 2016, 26(1): 236–249
CrossRef Google scholar
[4]
Xiao J, Hannuksela M M, Tillo T, Gabbouj M, Zhu C, Zhao Y. Scalable bit allocation between texture and depth views for 3-D video streaming over heterogeneous networks. IEEE Transactions on Circuits and Systems for Video Technology, 2015, 25(1): 139–152
CrossRef Google scholar
[5]
Hua K A, Cai Y, Sheu S. Patching: a multicast technique for true video-on-demand services. In: Proceedings of the 6th ACM International Conference on Multimedia. 1998, 191–200
CrossRef Google scholar
[6]
Dan A, Sitaram D, Shahabuddin P. Scheduling policies for an ondemand video server with batching. In: Proceedings of the 2nd ACM International Conference on Multimedia. 1994, 15–23
[7]
Pathan A M K, Buyya R. A taxonomy and survey of content delivery networks. Technical Report. 2007
[8]
Sahoo J, Salahuddin M, Glitho R, Elbiaze H, Ajib W. A survey on replica server placement algorithms for content delivery networks. IEEE Communications Surveys and Tutorials, 2017, 19(2): 1002–1026
CrossRef Google scholar
[9]
Wang M, Jayaraman P P, Ranjan R, Zhang M, Li E, Khan S, Pathan M, Georgeakopoulos D. An overview of cloud based content delivery networks: research dimensions and state-of-the-art. Transactions on Large-Scale Dataand Knowledge-Centered Systems, 2015: 131–158
[10]
Dilley J, Maggs B, Parikh J, Prokop H, Sitaraman R, Weihl B. Globally distributed content delivery. IEEE Internet Computing, 2002, 6(5): 50–58
CrossRef Google scholar
[11]
Goel U, Wittie M P, Steiner M. FasterWeb through client-assisted CDN server selection. In: Proceedings of the 24th International Conference on Computer Communication and Networks. 2015, 1–10
[12]
Tran H A, Hoceini S, Mellouk A, Perez J, Zeadally S. QoE-based server selection for content distribution networks. IEEE Transactions on Mobile Computing, 2014, 63(11): 2803–2815
CrossRef Google scholar
[13]
He J, Song W. Evolving to 5G: a fast and near-optimal request routing protocol for mobile core networks. In: Proceedings of IEEE Global Communications Conference. 2014, 4586–4591
CrossRef Google scholar
[14]
Taima K. Can we ever charge napster users? IEEE MultiMedia, 2002, 9(4): 76–81
CrossRef Google scholar
[15]
Zhang X Y, Liu J C, Li B, Yum Y S P. Coolstreaming/donet: a datadriven overlay network for peer-to-peer live media streaming. In: Proceedings of the 24th IEEE Annual Joint Conference of the IEEE Computer and Communications Societies. 2005, 2102–2111
CrossRef Google scholar
[16]
Silva A P C D, Leonardi E, Mellia M, Meo M. Chunk distribution in mesh-based large-scale P2P streaming systems: a fluid approach. IEEE Transactions on Parallel and Distributed Systems, 2011, 22(3): 451–463
CrossRef Google scholar
[17]
Saxena N, Sahu B J R, Han Y S. Traffic-aware energy optimization in green LTE cellular systems. IEEE Communications Letters, 2014, 18(1): 38–41
CrossRef Google scholar
[18]
Duan L, Huang J, Walrand J. Economic analysis of 4G upgrade timing. IEEE Transactions on Mobile Computing, 2015, 14(5): 975–989
CrossRef Google scholar
[19]
Agyapong P K, Iwamura M, Staehle D, Kiess W, Benjebbour A. Design considerations for a 5G network architecture. IEEE Communications Magazine, 2014, 52(11): 65–75
CrossRef Google scholar
[20]
Agiwal M, Roy A, Saxena N. Next generation 5G wireless networks: a comprehensive survey. IEEE Communications Surveys and Tutorials, 2016, 18(3): 1617–1655
CrossRef Google scholar
[21]
Cisco Inc. Cisco visual networking index: forecast and methodology. White Paper, 2016
[22]
Wang S L, Liu M, Cheng X Z, Li Z C, Huang J H, Chen B. Opportunistic routing in intermittently connected mobile P2P networks. IEEE Journal on Selected Areas in Communications, 2013, 31(9): 369–378
CrossRef Google scholar
[23]
Chen K, Shen H Y, Zhang H B. Leveraging social networks for P2P content-based file sharing in disconnected manets. IEEE Transactions on Mobile Computing, 2014, 13(2): 235–249
CrossRef Google scholar
[24]
Fanelli M, Foschini L, Corradi A, Boukerche A. Self-adaptive context data distribution with quality guarantees in mobile P2P networks. IEEE Journal on Selected Areas in Communications, 2013, 31(9): 115–131
CrossRef Google scholar
[25]
Siekkinen M, Hoque M A, Nurminen J K. Using viewing statistics to control energy and traffic overhead in mobile video streaming. IEEE/ACM Transactions on Networking, 2016, 24(3): 1489–1503
CrossRef Google scholar
[26]
Chung J M, Go D C. Stochastic vector mobility model for mobile and vehicular ad hoc network simulation. IEEE Transactions on Mobile Computing, 2012, 11(10): 1494–1507
CrossRef Google scholar
[27]
Zaidi Z R, Mark B L. Mobility tracking based on autoregressive models. IEEE Transactions on Mobile Computing, 2011, 10(1): 32–43
CrossRef Google scholar
[28]
Shen H Y, Li Z, Chen K. Social-P2P: an online social network based P2P file sharing system. IEEE Transactions on Parallel and Distributed Systems, 2015, 26(10): 2874–2889
CrossRef Google scholar
[29]
Le-Dang Q, McManis J, Muntean G M. Location-aware chord-based overlay for wireless mesh networks. IEEE Transactions on Vehicular Technology, 2014, 63(3): 1378–1387
CrossRef Google scholar
[30]
Xu C Q, Zhao F T, Guan J F, Zhang H K, Muntean G M. QoE-driven user-centric VoD services in urban multihomed P2P-based vehicular networks. IEEE Transactions on Vehicular Technology, 2013, 62(5): 2273–2289
CrossRef Google scholar
[31]
Chow C Y, Mokbel M F, Leong H V. On efficient and scalable support of continuous queries in mobile peer-to-peer environments. IEEE Transactions on Mobile Computing, 2011, 10(10): 1473–1487
CrossRef Google scholar
[32]
Jia S J, Xu C Q, Vasilakos A V, Guan J F, Zhang H K, Muntean G M. Reliability-oriented ant colony optimization-based mobile peer-to-peer VoD solution in MANETs.Wireless Networks, 2014, 20(5): 32–43
CrossRef Google scholar
[33]
Kim D, Kim E, Lee C. Efficient peer-to-peer overlay networks for mobile IPTV services. IEEE Transactions on Consumer Electronics, 2010, 56(4): 2303–2309
CrossRef Google scholar
[34]
Kubo H, Shinkuma R, Takahashi T. Mobile P2P multicast based on social network reducing psychological forwarding cost. In: Proceedings of IEEE Global Telecommunications Conference. 2010, 1–5
[35]
Xu C Q, Jia S J, Zhong L J, Zhang H K, Muntean G M. Ant-inspired mini-community-based solution for video-on-demand services in wireless mobile networks. IEEE Transactions on Vehicular Broadcasting, 2014, 60(2): 322–335
CrossRef Google scholar
[36]
Xu C Q, Jia S J, Wang M, Zhong L J, Zhang H K, Muntean G M. Performance-aware mobile community-based VoD streaming over vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 2015, 64(3): 1201–1217
CrossRef Google scholar
[37]
Xu C Q, Jia S J, Zhong L J, Muntean G M. Socially aware mobile peer-to-peer communications for community multimedia streaming services. IEEE Communications Magazine, 2015, 53(10): 150–156
CrossRef Google scholar
[38]
Jia S J, Xu C Q, Guan J F, Zhang H K, Muntean G M. A novel cooperative content fetching-based strategy to increase the quality of video delivery to mobile users in wireless networks. IEEE Transactions on Broadcasting, 2014, 60(2): 370–384
CrossRef Google scholar
[39]
Xu C Q, Li Z F, Li J L, Zhang H K, Muntean G M. Cross-layer fairnessdriven concurrent multipath video delivery over heterogeneous wireless networks. IEEE Transactions on Circuits and Systems for Video Technology, 2015, 25(7): 1175–1189
CrossRef Google scholar
[40]
Zhao T S, Liu Q, Chen C W. QoE in video transmission: a user experience-driven strategy. IEEE Communications Surveys and Tutorials, 2017, 19(1): 285–302
CrossRef Google scholar
[41]
Wallace T D, Shami A. Concurrent multipath transfer using SCTP: modelling and congestion window management. IEEE Transactions on Mobile Computing, 2014, 13(11): 2510–2523
CrossRef Google scholar
[42]
Huang C M, Lin M S. Multimedia streaming using partially reliable concurrent multipath transfer for multihomed networks. IET Communications, 2011, 5(5): 587–597
CrossRef Google scholar
[43]
Arianpoo N, Aydin I, Leung V C M. Network coding as a performance booster for concurrent multi-path transfer of data in multi-hop wireless networks. IEEE Transactions on Mobile Computing, 2017, 16(4): 1047–1058
CrossRef Google scholar
[44]
Wu J Y, Yuen C, Cheng B, Wang M, Chen J L. Energy-minimized multipath video transport to mobile devices in heterogeneous wireless networks. IEEE Journal on Selected Areas in Communications, 2016, 34(5): 1160–1178
CrossRef Google scholar
[45]
Bui D H, Lee K, Oh S, Shin I, Shin H, Woo H, Ban D. Greenbag: energy-efficient bandwidth aggregation for real-time streaming in heterogeneous mobile wireless networks. In: Proceedings of the 34th IEEE Real-Time Systems Symposium. 2013, 57–67
CrossRef Google scholar
[46]
Peng Q Y, Chen M H, Walid A, Low S. Energy efficient multipath TCP for mobile devices. In: Proceedings of ACM International Symposium on Mobile Ad Hoc Networking and Computing. 2014, 257–266
CrossRef Google scholar
[47]
Wu J Y, Cheng B, Yuen C, Shang Y L, Chen J L. Distortion-aware concurrent multipath transfer for mobile video streaming in heterogeneous wireless networks. IEEE Transactions on Mobile Computing, 2015, 14(4): 688–701
CrossRef Google scholar
[48]
Singh V, Ahsan S. MPRTP: multipath considerations for real-time media. In: Proceedings of ACM Multimedia Systems Conference. 2013, 190–201
CrossRef Google scholar
[49]
Xu C Q, Liu T J, Guan J F, Zhang H K, Muntean G M. CMT-QA: quality-aware adaptive concurrent multipath data transfer in heterogeneous wireless networks. IEEE Transactions on Mobile Computing, 2013, 12(11): 2193–2205
CrossRef Google scholar
[50]
Natarajan P, Ekiz N, Amer P D, Stewart R. Concurrent multipath transfer during path failure. Computer Communications, 2009, 32(15): 1577–1587
CrossRef Google scholar
[51]
Xu C Q, Wang P, Xiong C S, Wei X P, Muntean G M. Pipeline network coding-based multipath data transfer in heterogeneous wireless networks. IEEE Transactions on Broadcasting, 2016, 63(2): 376–390
CrossRef Google scholar
[52]
Xu C Q, Li Z F, Zhong L J, Zhang H K, Muntean G M. CMT-NC: improving the concurrent multipath transfer performance using network coding in wireless networks. IEEE Transactions on Vehicular Technology, 2016, 65(3): 1735–1751
CrossRef Google scholar
[53]
Amadeo M, Campolo C, Molinaro A. Information-centric networking for connected vehicles: a survey and future perspectives. IEEE Communications Magazine, 2016, 54(2): 98–104
CrossRef Google scholar
[54]
Ioannou A, Weber S. A survey of caching policies and forwarding mechanisms in information-centric networking. IEEE Communications Surveys and Tutorials, 2016, 18(4): 2847–2886
CrossRef Google scholar
[55]
Lederer S, Mueller C, Timmerer C, Hellwagner H. Adaptive multimedia streaming in information-centric networks. IEEE Network, 2014, 28(6): 91–96
CrossRef Google scholar
[56]
Zhang L X, Afanasyev A, Burke J, Jacobson V, Claffy K, Crowley P, Papadopoulos C, Wang L, Zhang B C. Named data networking. ACM SIGCOMM Computer Communication Review, 2014, 44(3): 66–73
CrossRef Google scholar
[57]
Grassi G, Pesavento D, Pau G, Vuyyuru R, Wakikawa R, Zhang L X. Vanet via named data networking. In: Proceedings of IEEE Conference on Computer Communications Workshops. 2014, 410–415
CrossRef Google scholar
[58]
Psaras I, Chai W K, Pavlou G. Probabilistic in-network caching for information-centric networks. In: Proceedings of the 2nd Edition of the ICN Workshop on Information-centric Networking. 2012, 55–60
CrossRef Google scholar
[59]
Hu X, Gong J. Opportunistic on-path caching for named data networking. IEICE Transactions on Communication, 2014, 97(11): 2360–2367
CrossRef Google scholar
[60]
Xu C Q, Quan W, Zhang H K, Grieco L A. GrIMS: green informationcentric multimedia streaming framework in vehicular ad hoc networks. IEEE Transactions on Circuits and Systems for Video Technology, 2018, 28(2): 483–498
[61]
Xu C Q, Quan W, Vasilakos A V, Zhang H K, Muntean G M. Information-centric cost-efficient optimization for multimedia content delivery in mobile vehicular networks. Computer Communications, 2017, 99: 93–106
[62]
Lu Y, Li X, Yu Y T, Gerla M. Information-centric delay-tolerant mobile ad-hoc networks. In: Proceedings of IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). 2014, 428–433
CrossRef Google scholar
[63]
Ahmed S H, Bouk S H, Kim D. RUFS: robust forwarder selection in vehicular content-centric networks. IEEE Communications Letters, 2015, 19(9): 1616–1619
CrossRef Google scholar
[64]
Liu H, Lu J W, Feng J J, Zhou J.Learning deep sharable and structural detectors for face alignment. IEEE Transactions on Image Processing, 2017, 26(4): 1666–1678
CrossRef Google scholar
[65]
Rahmani H, Mian A, Shah M. Learning a deep model for human action recognition from novel viewpoints. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40(3): 667–681
[66]
Li Y C, Cao L L, Zhu J, Luo J B. Mining fashion outfit composition using an end-to-end deep learning approach on set data. IEEE Transactions on Multimedia, 2017, 19(8): 1946–1955
[67]
Shi H, Xu M H, Li R. Deep learning for household load forecasting — a novel pooling deep RNN. IEEE Transactions on Smart Grid, 2018, 9(5): 5271–5280
[68]
Zhang G, Wen Y G, Zhu J, Chen Q H. On file delay minimization for content uploading to media cloud via collaborative wireless network. In: Proceedings of International Conference on Wireless Communications and Signal Processing. 2011, 1–6
CrossRef Google scholar
[69]
Tang J H, Tay W P, Wen Y G. Dynamic request redirection and elastic service scaling in cloud-centric media networks. IEEE Transactions on Multimedia, 2014, 16(5): 1434–1445
CrossRef Google scholar
[70]
Yang M, Cai J F, Wen Y G, Foh C H. Complexity-rate-distortion evaluation of video encoding for cloud media computing. In: Proceedings of the 17th IEEE International Conference on Networks. 2011, 25–29
[71]
Wu Y, Wu C, Li B, Qiu X J, Lau F C M. Cloudmedia: when cloud on demand meets video on demand. In: Proceedings of the 31st International Conference on Distributed Computing Systems. 2011, 268–277
CrossRef Google scholar

RIGHTS & PERMISSIONS

2018 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
AI Summary AI Mindmap
PDF(1689 KB)

Accesses

Citations

Detail

Sections
Recommended

/