Paper Info
Title
A Multi-Objective Particle Swarm Optimization Data Scheduling Algorithm For Peer-To-Peer Video Streaming
Abstract
In P2P (Peer-to-Peer) video streaming systems using unstructured mesh, data scheduling is an important factor on system performance. An optimal data scheduling scheme should achieve two objectives ideally. The first objective is to optimize the perceived video quality of peers. The second objective is to maximize the network throughput, i.e., utilize the upload bandwidth of peers maximally. However, the optimized perceived video quality may not bring a maximized network throughput, and vice versa. In the paper, to better achieve the two objectives simultaneously, we formulate the data scheduling problem as a multi-objective optimization problem. To solve the multi-objective optimization problem, we propose a multi-objective particle swarm optimization data scheduling algorithm by encoding the peers' neighbors as the locations of the particles. Through simulations, we demonstrate the proposed algorithm outperforms other algorithms in terms of the perceived video quality and the utilization of peers' upload capacity.
Year
Venue
Keywords
2017
2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD)
Peer-to-Peer, streaming, data scheduling, multi-objective optimization, multi-objective particle swarm optimization
Field
DocType
Citations 
Particle swarm optimization,Peer-to-peer,Computer science,Scheduling (computing),Upload,Algorithm,Throughput,Video quality,Optimization problem,Encoding (memory)
Conference
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Pingshan Liu100.68
Xiaoyi Xiong201.01
Guimin Huang369.26
Yimin Wen431.38