Paper Info
Title
Clonal Selection Based Genetic Algorithm For Workflow Service Selection
Abstract
Quality of Service (QoS) aware service selection of workflows is a very important aspect for service-oriented systems. The selection based on QoS allows the user to include also non-functional attributes in their query, such as availability and reliability. Several exact methods have been proposed in the past, however, given that the workflow selection problem is NP-hard, approximate algorithms can be used to find suboptimal solutions for requested workflows. Genetic algorithm is one such method that can find approximate solutions in the form of services selected. In this paper, we propose an improved version of the standard genetic algorithm approach by making use of the clonal selection principle from artificial immune systems. Experimental results show that the clonal selection based genetic algorithm achieves much higher fitness values for the workflow selection problem than standard genetic algorithm.
Year
DOI
Venue
2012
10.1109/CEC.2012.6256465
2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
Keywords
Field
DocType
genetic algorithms,web services,service oriented architecture,reliability,concrete,artificial immune systems,quality of service,immune system
Data mining,Artificial immune system,Workflow technology,Computer science,Quality of service,Artificial intelligence,Quality control and genetic algorithms,Clonal selection,Workflow,Workflow management system,Machine learning,Genetic algorithm
Conference
Citations 
PageRank 
References 
3
0.39
0
Authors
1
Name
Order
Citations
PageRank
Simone A Ludwig11309179.41