Paper Info
Title
A Multi-objective Optimization Data Scheduling Algorithm for P2P Video Streaming.
Abstract
In P2P video streaming, each peer requests its wanted streaming data from others and responses others' requests by its data scheduling algorithm. Recent years, some data scheduling algorithms are proposed either to optimize the perceived video quality, or to optimize the network throughput. However, optimizing the perceived video quality may lead to low utilization of the senders' upload capacity. On the other hand, optimizing the network throughput may lead to the degrading perceived quality, for some emergent data may not be transmitted in time. In this paper, to improve the two objectives simultaneously, we formulate the data scheduling problem as a multi-objective model. In the formulation, we not only consider the segment quality and emergency which affect the perceived video quality, but also consider the rarity of the segments, which influences the network throughput. Then, we propose a distributed data scheduling algorithm to solve the multi-objective problem in polynomial time. Through simulations, we show the proposed algorithm outperforms other conventional algorithms in perceived video quality and utilization of peers' upload capacity.
Year
DOI
Venue
2017
10.1007/978-981-10-6388-6_16
Communications in Computer and Information Science
Keywords
Field
DocType
Peer-to-Peer video streaming,Data scheduling,Throughput,Quality optimization
Fair-share scheduling,Computer science,Video streaming,Upload,Algorithm,Multi-objective optimization,Throughput,Time complexity,Video quality,Data scheduling
Conference
Volume
ISSN
Citations 
728
1865-0929
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Pingshan Liu143.81
Xiaoyi Xiong201.01
Guimin Huang369.26