Paper Info
Title
QoS multicast routing using a quantum-behaved particle swarm optimization algorithm
Abstract
QoS multicast routing in networks is a very important research issue in networks and distributed systems. It is also a challenging and hard problem for high-performance networks of the next generation. Due to its NP-completeness, many heuristic methods have been employed to solve the problem. This paper proposes the modified quantum-behaved particle swarm optimization (QPSO) method for QoS multicast routing. In the proposed method, QoS multicast routing is converted into an integer programming problem with QoS constraints and is solved by the QPSO algorithm combined with loop deletion operation. The QPSO-based routing method, along with the routing algorithms based on particle swarm optimization (PSO) and genetic algorithm (GA), is tested on randomly generated network topologies for the purpose of performance evaluation. The simulation results show the efficiency of the proposed method on QoS the routing problem and its superiority to the methods based on PSO and GA.
Year
DOI
Venue
2011
10.1016/j.engappai.2010.08.001
Eng. Appl. of AI
Keywords
Field
DocType
routing problem,qpso-based routing method,qpso algorithm,hard problem,qos multicast routing,genetic algorithm,quantum-behaved particle swarm optimization,integer programming problem,heuristic method,qos constraint,network topology,quality of service,distributed system,particle swarm optimization,integer programming
Link-state routing protocol,Equal-cost multi-path routing,Mathematical optimization,Multipath routing,Dynamic Source Routing,Computer science,Static routing,Hierarchical routing,Destination-Sequenced Distance Vector routing,Algorithm,Wireless Routing Protocol,Distributed computing
Journal
Volume
Issue
ISSN
24
1
Engineering Applications of Artificial Intelligence
Citations 
PageRank 
References 
22
0.83
16
Authors
5
Name
Order
Citations
PageRank
Jun Sun120712.29
Wei Fang233919.89
Xiaojun Wu323011.79
Zhenping Xie4433.01
Wenbo Xu537023.34