Paper Info
Title
A web service composition algorithm based on global QoS optimizing with MOCACO
Abstract
Web services composition has gained a considerable momentum as a means to create and streamline B2B collaborations within and across organizational boundaries. This paper focuses on the web services composition and provides a novel selection algorithm based on global QoS optimizing and Multi-objective Chaos Ant Colony Optimization (MOCACO). Firstly, the web services selection model with QoS global optimization is converted into a multi-objective optimization problem. Furthermore, the MOCACO is used to select the service and optimize QoS to satisfy the user constraints. During the optimizing procedure, the random and ergodic chaos variable is used to make an optimal search, it overcomes the problem of low efficiency and easily being in a partial optimization that ant colony algorithm brings. The simulation shows that the MOCACO is more efficient and effective than Multi-objective Genetic Algorithm (MOGA) applied to services composition. © Springer-Verlag Berlin Heidelberg 2010.
Year
DOI
Venue
2010
10.1007/978-3-642-13136-3_22
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Keywords
Field
DocType
null
Ant colony optimization algorithms,Mathematical optimization,Global optimization,Computer science,Selection algorithm,Meta-optimization,Quality of service,Optimization problem,Genetic algorithm,Distributed computing,Metaheuristic
Conference
Volume
Issue
ISSN
6082 LNCS
PART 2
16113349
ISBN
Citations 
PageRank 
3-642-13135-2
17
1.07
References 
Authors
5
2
Name
Order
Citations
PageRank
Li Wang1224.52
He Yan-xiang2171.41