A Stochastic Optimization Approach for Dynamic Adaptive Scalable Video Streaming over NDN
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- 英文论文题名：A Stochastic Optimization Approach for Dynamic Adaptive Scalable Video Streaming over NDN
- 论文作者：Xiangyang Wu ; Xiaobin Tan ; Yunfeng Shao ; Jiawei Ni ; Jin Zhu
- 英文论文作者：Xiangyang Wu ; Xiaobin Tan ; Yunfeng Shao ; Jiawei Ni ; Jin Zhu ; Laboratory for Future Networks ; University of Science and Technology of China
- 年：2017
- 作者机构：Laboratory for Future Networks,University of Science and Technology of China;
- 英文论文关键词：Named Data Networking ; Scalable Video Streaming ; Stochastic Optimization
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP393.0
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：550k
- 原文格式：D
- 会议级别：全国
摘要
Named Data Networking(NDN) is a general proposed network layer protocol which offers a set of rich functionality:in-network storage, multi-path forwarding, and data-centric security. The cache and multi-path feature improves the efficiency of transmission but increases the difficulty of the bandwidth estimation. In this paper, a dynamic layer switching strategy using Lyapunov Optimization is proposed for dynamic adaptive scalable video streaming over NDN. It aims for optimizing long-term quality-of-experience(QoE) of users via maximizing video quality subject to a constraint on playback smoothness, interruption and fluctuation. The proposed algorithm does not require a priori knowledge of the network bandwidth dynamics, and is capable of operating online with the client's currently available information. Experimental results indicate that our algorithm performs better than others in NDN.
Named Data Networking(NDN) is a general proposed network layer protocol which offers a set of rich functionality:in-network storage, multi-path forwarding, and data-centric security. The cache and multi-path feature improves the efficiency of transmission but increases the difficulty of the bandwidth estimation. In this paper, a dynamic layer switching strategy using Lyapunov Optimization is proposed for dynamic adaptive scalable video streaming over NDN. It aims for optimizing long-term quality-of-experience(QoE) of users via maximizing video quality subject to a constraint on playback smoothness, interruption and fluctuation. The proposed algorithm does not require a priori knowledge of the network bandwidth dynamics, and is capable of operating online with the client's currently available information. Experimental results indicate that our algorithm performs better than others in NDN.
Named Data Networking(NDN) is a general proposed network layer protocol which offers a set of rich functionality:in-network storage, multi-path forwarding, and data-centric security. The cache and multi-path feature improves the efficiency of transmission but increases the difficulty of the bandwidth estimation. In this paper, a dynamic layer switching strategy using Lyapunov Optimization is proposed for dynamic adaptive scalable video streaming over NDN. It aims for optimizing long-term quality-of-experience(QoE) of users via maximizing video quality subject to a constraint on playback smoothness, interruption and fluctuation. The proposed algorithm does not require a priori knowledge of the network bandwidth dynamics, and is capable of operating online with the client's currently available information. Experimental results indicate that our algorithm performs better than others in NDN.
引文
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[9]Jin Y,Wen Y.PAINT:Partial in-network transcoding for adaptive streaming in information centric network[C]//2014 IEEE22nd International Symposium of Quality of Service(IWQo S).IEEE,2014:208-217.
[10]Yu Y T,Bronzino F,Fan R,et al.Congestion-aware edge caching for adaptive video streaming in information-centric networks[C]//2015 12th Annual IEEE Consumer Communications and Networking Conference(CCNC).IEEE,2015:588-596.
[11]Posch D,Kreuzberger C,Rainer B,et al.Using innetwork adaptation to tackle inefficiencies caused by dash in information-centric networks[C]//Proceedings of the 2014Workshop on Design,Quality and Deployment of Adaptive Video Streaming.ACM,2014:25-30.
[12]Petrangeli S,Claeys M,Latr S,et al.A multi-agent QLearning-based framework for achieving fairness in HTTP Adaptive Streaming[C]//2014 IEEE Network Operations and Management Symposium(NOMS).IEEE,2014:1-9.
[13]Mastorakis S,Afanasyev A,Moiseenko I,et al.ndn SIM 2.0:A new version of the NDN simulator for NS-3[J].NDN,Technical Report NDN-0028,2015.
[14]Kreuzberger C,Posch D,Hellwagner H.A scalable video coding dataset and toolchain for dynamic adaptive streaming over HTTP[C]//Proceedings of the 6th ACM Multimedia Systems Conference.ACM,2015:213-218.
[15]NDN team.NDN Forwarding Daemon,2014.http://nameddata.net/doc/NFD/current/
[16]Rainer B,Posch D,Hellwagner H.Investigating the Performance of Pull-Based Dynamic Adaptive Streaming in NDN[J].2016,34(8):1-1.
[2]Jacobson V,Smetters D K,Thornton J D,et al.Networking named content[C]//Proceedings of the 5th international conference on Emerging networking experiments and technologies.ACM,2009:1-12.
[3]Sodagar I.The MPEG-DASH Standard for Multimedia Streaming Over the Internet[J].IEEE Multi Media,2011,4(18):62-67.
[4]Schwarz H,Marpe D,Wiegand T.Overview of the scalable video coding extension of the H.264/AVC standard[J].IEEE Transactions on circuits and systems for video technology,2007,17(9):1103-1120.
[5]Wiegand T,Sullivan G J,Bjontegaard G,et al.Overview of the H.264/AVC video coding standard[J].IEEE Transactions on circuits and systems for video technology,2003,13(7):560-576.
[6]Snchez Y,Schierl T,Hellge C,et al.Improved caching for HTTP-based video on demand using scalable video coding[C]//2011 IEEE Consumer Communications and Networking Conference(CCNC).IEEE,2011:595-599.
[7]Neely M J.Stochastic network optimization with application to communication and queueing systems[J].Synthesis Lectures on Communication Networks,2010,3(1):1-211.
[8]Grandl R,Su K,Westphal C.On the interaction of adaptive video streaming with content-centric networking[C]//201320th International Packet Video Workshop.IEEE,2013:1-8.
[9]Jin Y,Wen Y.PAINT:Partial in-network transcoding for adaptive streaming in information centric network[C]//2014 IEEE22nd International Symposium of Quality of Service(IWQo S).IEEE,2014:208-217.
[10]Yu Y T,Bronzino F,Fan R,et al.Congestion-aware edge caching for adaptive video streaming in information-centric networks[C]//2015 12th Annual IEEE Consumer Communications and Networking Conference(CCNC).IEEE,2015:588-596.
[11]Posch D,Kreuzberger C,Rainer B,et al.Using innetwork adaptation to tackle inefficiencies caused by dash in information-centric networks[C]//Proceedings of the 2014Workshop on Design,Quality and Deployment of Adaptive Video Streaming.ACM,2014:25-30.
[12]Petrangeli S,Claeys M,Latr S,et al.A multi-agent QLearning-based framework for achieving fairness in HTTP Adaptive Streaming[C]//2014 IEEE Network Operations and Management Symposium(NOMS).IEEE,2014:1-9.
[13]Mastorakis S,Afanasyev A,Moiseenko I,et al.ndn SIM 2.0:A new version of the NDN simulator for NS-3[J].NDN,Technical Report NDN-0028,2015.
[14]Kreuzberger C,Posch D,Hellwagner H.A scalable video coding dataset and toolchain for dynamic adaptive streaming over HTTP[C]//Proceedings of the 6th ACM Multimedia Systems Conference.ACM,2015:213-218.
[15]NDN team.NDN Forwarding Daemon,2014.http://nameddata.net/doc/NFD/current/
[16]Rainer B,Posch D,Hellwagner H.Investigating the Performance of Pull-Based Dynamic Adaptive Streaming in NDN[J].2016,34(8):1-1.