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NCTM: A Novel Coded Transmission Mechanism for Short Video Deliveries

Published: 13 May 2024 Publication History

Abstract

With the rapid popularity of short video applications, a large number of short video transmissions occupy the bandwidth, placing a heavy load on the Internet. Due to the extensive number of short videos and the predominant service for mobile users, traditional approaches (e.g., CDN delivery, edge caching) struggle to achieve the expected performance, leading to a significant number of redundant transmissions. In order to reduce the amount of traffic, we design a Novel Coded Transmission Mechanism (NCTM), which transmits XOR-coded data instead of the original video content. NCTM caches the short videos that users have already watched in user devices, and encodes, multicasts, and decodes XOR-coded files separately at the server, edge nodes, and clients, with the assistance of cached content. This approach enables NCTM to deliver more short video data given the limited bandwidth. Our extensive trace-driven simulations show how NCTM reduces network load by 3.02%-14.75%, cuts peak traffic by 23.01%, and decreases rebuffering events by 43%-85% in comparison to a CDN-supported scheme and a naive edge caching scheme. Additionally, NCTM also increases the user's buffered video duration by 1.21x-13.53x, ensuring improved playback smoothness.

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References

[1]
The official website of tiktok. (2023, Jul 26).
[2]
The official website of YouTube Shorts. (2023, Jul 26).
[3]
TikTok: Thanks a billion! (2023, Jun 24).
[4]
YouTube Shorts Video-Making App Now Receiving 3.5 Billion Daily Views. (2023, Jun 24).
[5]
TikTok Revenue and Usage Statistics (2022). (2023, Jun 24).
[6]
Gang Peng. Cdn: Content distribution network. arXiv preprint cs/0411069, 2004.
[7]
Fahao Chen, Peng Li, Deze Zeng, and Song Guo. Edge-assisted short video sharing with guaranteed quality-of-experience. IEEE Transactions on Cloud Computing, 2021.
[8]
Sem C. Borst, Varun Gupta, and Anwar Walid. Distributed caching algorithms for content distribution networks. In Conference on Information Communications, 2010.
[9]
Hanling Wang, Qing Li, Heyang Sun, Zuozhou Chen, Yingqian Hao, Junkun Peng, Zhenhui Yuan, Junsheng Fu, and Yong Jiang. Vabus: Edge-cloud real-time video analytics via background understanding and subtraction. IEEE Journal on Selected Areas in Communications, 41(1):90--106, 2022.
[10]
Ying Chen, Qing Li, Aoyang Zhang, Longhao Zou, Yong Jiang, Zhimin Xu, Junlin Li, and Zhenhui Yuan. Higher quality live streaming under lower uplink bandwidth: an approach of super-resolution based video coding. In Proceedings of the 31st ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, pages 74--81, 2021.
[11]
Ju Ren, Deyu Zhang, Shiwen He, Yaoxue Zhang, and Tao Li. A survey on endedge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet. ACM Computing Surveys (CSUR), 52(6):1--36, 2019.
[12]
Yushan Siriwardhana, Pawani Porambage, Madhusanka Liyanage, and Mika Ylianttila. A survey on mobile augmented reality with 5g mobile edge computing: Architectures, applications, and technical aspects. IEEE Communications Surveys & Tutorials, 23(2):1160--1192, 2021.
[13]
Xiaojie Wang, Jiameng Li, Zhaolong Ning, Qingyang Song, Lei Guo, Song Guo, and Mohammad S Obaidat. Wireless powered mobile edge computing networks: A survey. ACM Computing Surveys, 2023.
[14]
Muhammad Yasir, Sardar Khaliq uz Zaman, Tahir Maqsood, Faisal Rehman, and Saad Mustafa. Copup: Content popularity and user preferences aware content caching framework in mobile edge computing. Cluster Computing, 26(1):267--281, 2023.
[15]
Xiaobo Zhou, Zhihui Ke, and Tie Qiu. Recommendation-driven multi-cell cooperative caching: A multi-agent reinforcement learning approach. IEEE Transactions on Mobile Computing, 2023.
[16]
Nhu-Ngoc Dao, Anh-Tien Tran, Ngo Hoang Tu, Tran Thien Thanh, Vo Nguyen Quoc Bao, and Sungrae Cho. A contemporary survey on live video streaming from a computation-driven perspective. ACM Computing Surveys, 54(10s):1--38, 2022.
[17]
Shilpa Budhkar and Venkatesh Tamarapalli. An overlay management strategy to improve qos in cdn-p2p live streaming systems. Peer-to-peer networking and applications, 13:190--206, 2020.
[18]
Reza Farahani, Abdelhak Bentaleb, Ekrem Çetinkaya, Christian Timmerer, Roger Zimmermann, and Hermann Hellwagner. Hybrid p2p-cdn architecture for live video streaming: An online learning approach. In GLOBECOM 2022--2022 IEEE Global Communications Conference, pages 1911--1917. IEEE, 2022.
[19]
Mohammad Ali Maddah-Ali and Urs Niesen. Fundamental limits of caching. IEEE Transactions on information theory, 60(5):2856--2867, 2014.
[20]
Mohammad Ali Maddah-Ali and Urs Niesen. Decentralized coded caching attains order-optimal memory-rate tradeoff. IEEE/ACM Transactions On Networking, 23(4):1029--1040, 2014.
[21]
Urs Niesen and Mohammad Ali Maddah-Ali. Coded caching with nonuniform demands. IEEE Transactions on Information Theory, 63(2):1146--1158, 2016.
[22]
Ramtin Pedarsani, Mohammad Ali Maddah-Ali, and Urs Niesen. Online coded caching. IEEE/ACM Transactions on Networking, 24(2):836--845, 2015.
[23]
Jens Gramm, Jiong Guo, Falk Hüffner, and Rolf Niedermeier. Data reduction and exact algorithms for clique cover. ACM J. Exp. Algorithmics, 13, feb 2009.
[24]
Marek Cygan, Marcin Pilipczuk, and Michal Pilipczuk. Known algorithms for edge clique cover are probably optimal. SIAM Journal on Computing, 45(1):67--83, 2016.
[25]
Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao, and Tat-Seng Chua. Kuairec: A fully-observed dataset and insights for evaluating recommender systems. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pages 540--550, 2022.
[26]
Babak Bashari Rad, Harrison John Bhatti, and Mohammad Ahmadi. An introduction to docker and analysis of its performance. International Journal of Computer Science and Network Security (IJCSNS), 17(3):228, 2017.
[27]
Zheng Chang, Yunan Gu, Zhu Han, Xianfu Chen, and Tapani Ristaniemi. Contextaware data caching for 5g heterogeneous small cells networks. In 2016 IEEE International Conference on Communications (ICC), pages 1--6. IEEE, 2016.
[28]
N Golzerai, K Shanmugam, AG Dimakis, AF Molisch, and G Caire. Femtocaching: wireless video content delivery through distributed caching helpers. In Proc. IEEE INFO COM, 2012.
[29]
Zhuang Chen, Qian He, Zhifei Mao, Hwei-Ming Chung, and Sabita Maharjan. A study on the characteristics of douyin short videos and implications for edge caching. In Proceedings of the ACM Turing Celebration Conference - China, ACM TURC '19, New York, NY, USA, 2019. Association for Computing Machinery.
[30]
Yu Guan, Xinggong Zhang, and Zongming Guo. Prefcache: Edge cache admission with user preference learning for video content distribution. IEEE Transactions on Circuits and Systems for Video Technology, 31(4):1618--1631, 2021.
[31]
Fangxin Wang, Feng Wang, Jiangchuan Liu, Ryan Shea, and Lifeng Sun. Intelligent video caching at network edge: A multi-agent deep reinforcement learning approach. In IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, pages 2499--2508, 2020.
[32]
Mingyue Ji, Giuseppe Caire, and Andreas F Molisch. Fundamental limits of distributed caching in d2d wireless networks. In 2013 IEEE Information Theory Workshop (ITW), pages 1--5. IEEE, 2013.
[33]
Mingyue Ji, Giuseppe Caire, and Andreas F Molisch. Wireless device-to-device caching networks: Basic principles and system performance. IEEE Journal on Selected Areas in Communications, 34(1):176--189, 2015.
[34]
Sepandar D Kamvar, Mario T Schlosser, and Hector Garcia-Molina. The eigentrust algorithm for reputation management in p2p networks. In Proceedings of the 12th international conference on World Wide Web, pages 640--651, 2003.
[35]
Alexander Pyattaev, Olga Galinina, Sergey Andreev, Marcos Katz, and Yevgeni Koucheryavy. Understanding practical limitations of network coding for assisted proximate communication. IEEE Journal on Selected Areas in Communications, 33(2):156--170, 2014.
[36]
Qi Liu. A brief discussion on p2p network file transfer. Science, education and literature, (3):182--185, 2016.
[37]
Tang, Ming, Pang, Haitian, Huang, Jianwei, Sun, Lifeng, Gao, and Lin. Optimizations and economics of crowdsourced mobile streaming. IEEE Communications Magazine: Articles, News, and Events of Interest to Communications Engineers, 55(5):21--27, 2017.
[38]
Tz-Heng Hsu and Yao-Min Tung. A social-aware p2p video transmission strategy for multimedia iot devices. IEEE Access, 8:95574--95584, 2020.
[39]
Thomas Stockhammer. Dynamic adaptive streaming over http--standards and design principles. In Proceedings of the second annual ACM conference on Multimedia systems, pages 133--144, 2011.
[40]
Dilip Kumar Krishnappa, Divyashri Bhat, and Michael Zink. Dashing youtube: An analysis of using dash in youtube video service. In 38th Annual IEEE Conference on Local Computer Networks, pages 407--415. IEEE, 2013.
[41]
Zhuqi Li, Yaxiong Xie, Ravi Netravali, and Kyle Jamieson. Dashlet: Taming swipe uncertainty for robust short video streaming. 2022.
[42]
MAWI Working Group Traffic Archive. (2023, Jul 26).
[43]
Download link for the FCC18 dataset. (2023, July 7).
[44]
Ravi Netravali, Anirudh Sivaraman, Somak Das, Ameesh Goyal, Keith Winstein, James Mickens, and Hari Balakrishnan. Mahimahi: accurate {Record-and-Replay} for {HTTP}. In 2015 USENIX Annual Technical Conference (USENIX ATC, pages 417--429, 2015.
[45]
Alberto Caprara, Paolo Toth, and Matteo Fischetti. Algorithms for the set covering problem. Annals of Operations Research, 98(1--4):353--371, 2000.
[46]
Harry R Lewis. Michael r. πgarey and david s. johnson. computers and intractability. a guide to the theory of np-completeness. wh freeman and company, san francisco1979, x 338 pp. The Journal of Symbolic Logic, 48(2):498--500, 1983.
[47]
Mallesham Dasari, Kumara Kahatapitiya, Samir R Das, Aruna Balasubramanian, and Dimitris Samaras. Swift:Adaptive video streaming with layered neural codecs. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22), pages 103--118, 2022.
[48]
Yunzhuo Liu, Bo Jiang, Tian Guo, Ramesh K. Sitaraman, Don Towsley, and Xinbing Wang. Grad: Learning for overhead-aware adaptive video streaming with scalable video coding. In Proceedings of the 28th ACMInternational Conference on Multimedia, MM '20, page 349--357, New York, NY, USA, 2020. Association for Computing Machinery.
[49]
Hongzi Mao, Ravi Netravali, and Mohammad Alizadeh. Neural adaptive video streaming with pensieve. In the Conference of the ACM Special Interest Group, 2017.
[50]
Xiaoqi Yin, Abhishek Jindal, Vyas Sekar, and Bruno Sinopoli. A control-theoretic approach for dynamic adaptive video streaming over http. In Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication, pages 325--338, 2015.

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    cover image ACM Conferences
    WWW '24: Proceedings of the ACM Web Conference 2024
    May 2024
    4826 pages
    ISBN:9798400701719
    DOI:10.1145/3589334
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    New York, NY, United States

    Publication History

    Published: 13 May 2024

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    Author Tags

    1. client-side cache
    2. coded transmission
    3. short video delivery

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    • Research-article

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    • National Key R\&D Program of China
    • Shenzhen Key Lab of Software Defined Networking
    • Major Key Project of PCL
    • Science Foundation Ireland

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    WWW '24
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    WWW '24: The ACM Web Conference 2024
    May 13 - 17, 2024
    Singapore, Singapore

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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