A Stochastic Optimization Approach for Dynamic Adaptive Scalable Video Streaming over NDN

被引:0
|
作者
Wu, Xiangyang [1 ]
Tan, Xiaobin [1 ]
Shao, Yunfeng [1 ]
Ni, Jiawei [1 ]
Zhu, Jin [1 ]
机构
[1] Univ Sci & Technol China, Lab Future Networks, Hefei 230027, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
Named Data Networking; Scalable Video Streaming; Stochastic Optimization; STANDARD;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
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.
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页码:2326 / 2331
页数:6
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