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Dynamic resource allocation for scalable video multirate multicast over wireless networks

Dynamic resource allocation for scalable video multirate multicast over wireless networks
Dynamic resource allocation for scalable video multirate multicast over wireless networks
Aided by scalable video coding, multirate multicast has become a promising technique of providing differentiated quality of experience (QoE) for massive numbers of video subscribers operating in heterogeneous channel conditions. Nevertheless, due to the time-varying nature of wireless channels and the subscribers’ diverse requirements, it is challenging to dynamically control the video rate in the light of the available radio resource to achieve the best QoE. To elaborate a little further, the time scale of resource scheduling is of short-term nature, which determines the short-term video quality variation, but from a service provider’s perspective the design objective is to optimize the long-term QoE for all subscribers. Despite its importance, this problem has not been considered before. Explicitly, we formulated this problem as a time-averaged stochastic optimization problem which avoids the impact of both the short- term channel quality fluctuation and that of the video bitrates, whilst maintaining both inter- and intra- group fairness. The stratified structure of the problem inspires us to decompose it into a two-phase optimization: coarse grained assignment for each user group and fine grained assignment for each subgroup. We propose an adaptive multicast algorithm based on Lyapunov’s optimization theory for solving this problem, by striking a compelling trade-off between the system’s utility and its queue stability. We quantify the achievable performance of our proposed solution based on realistic video traces.
Multirate multicast, resource assignment, scalable video coding, wireless network
0018-9545
10227-10241
Chen, Shuangwu
7365b26b-794f-40f1-b620-df39462626aa
Yang, Bowen
0815b1fe-226e-4549-a8e2-2b5ebf182b80
Yang, Jian
a95e75db-6340-4085-af35-54e655b46b6f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, Shuangwu
7365b26b-794f-40f1-b620-df39462626aa
Yang, Bowen
0815b1fe-226e-4549-a8e2-2b5ebf182b80
Yang, Jian
a95e75db-6340-4085-af35-54e655b46b6f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, Shuangwu, Yang, Bowen, Yang, Jian and Hanzo, Lajos (2020) Dynamic resource allocation for scalable video multirate multicast over wireless networks. IEEE Transactions on Vehicular Technology, 69 (9), 10227-10241, [9122408]. (doi:10.1109/TVT.2020.3004048).

Record type: Article

Abstract

Aided by scalable video coding, multirate multicast has become a promising technique of providing differentiated quality of experience (QoE) for massive numbers of video subscribers operating in heterogeneous channel conditions. Nevertheless, due to the time-varying nature of wireless channels and the subscribers’ diverse requirements, it is challenging to dynamically control the video rate in the light of the available radio resource to achieve the best QoE. To elaborate a little further, the time scale of resource scheduling is of short-term nature, which determines the short-term video quality variation, but from a service provider’s perspective the design objective is to optimize the long-term QoE for all subscribers. Despite its importance, this problem has not been considered before. Explicitly, we formulated this problem as a time-averaged stochastic optimization problem which avoids the impact of both the short- term channel quality fluctuation and that of the video bitrates, whilst maintaining both inter- and intra- group fairness. The stratified structure of the problem inspires us to decompose it into a two-phase optimization: coarse grained assignment for each user group and fine grained assignment for each subgroup. We propose an adaptive multicast algorithm based on Lyapunov’s optimization theory for solving this problem, by striking a compelling trade-off between the system’s utility and its queue stability. We quantify the achievable performance of our proposed solution based on realistic video traces.

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Accepted/In Press date: 15 June 2020
e-pub ahead of print date: 22 June 2020
Published date: September 2020
Additional Information: Funding Information: Manuscript received January 8, 2020; revised April 23, 2020 and June 2, 2020; accepted June 14, 2020. Date of publication June 22, 2020; date of current version October 13, 2020. This work was supported in part by the Fundamental Research Funds for the Central Universities (WK2100000009), in part the Anhui Provincial Natural Science Foundation (1908085QF266), and in part the Youth Innovation Promotion Association CAS (CX2100107001) and in part the Anhui Special Support Program. Lajos Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/N004558/1, EP/P034284/1, EP/P034284/1, EP/P003990/1 (COALESCE), of the Royal Society’s Global Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom. The review of this article was coordinated by Prof. A. L. Grieco. (Corresponding author: Lajos Hanzo.) Shuangwu Chen, Bowen Yang, and Jian Yang are with the School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China (e-mail: chensw@ustc.edu.cn; ybw92@mail.ustc.edu.cn; jianyang@ustc.edu.cn). Publisher Copyright: © 1967-2012 IEEE.
Keywords: Multirate multicast, resource assignment, scalable video coding, wireless network

Identifiers

Local EPrints ID: 441773
URI: http://eprints.soton.ac.uk/id/eprint/441773
ISSN: 0018-9545
PURE UUID: cdf05184-64e4-46ae-adf3-1add0f939b4c
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 26 Jun 2020 16:41
Last modified: 06 Oct 2022 01:33

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Contributors

Author: Shuangwu Chen
Author: Bowen Yang
Author: Jian Yang
Author: Lajos Hanzo ORCID iD

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