A Novel Ant Colony Optimization Algorithm for Large Scale QoS-Based Service Selection Problem
Joint Authors
Yin, Hao
Zhang, Changsheng
Zhang, Bin
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
To tackle the large scale QoS-based service selection problem, a novel efficient clustering guided ant colony service selection algorithm called CASS is proposed in this paper.
In this algorithm, a skyline query process is used to filter the candidates related to each service class, and a clustering based shrinking process is used to guide the ant to the search directions.
We evaluate our approach experimentally using standard real datasets and synthetically generated datasets and compared it with the recently proposed related service selection algorithms.
It reveals very encouraging results in terms of the quality of solution and the processing time required.
American Psychological Association (APA)
Zhang, Changsheng& Yin, Hao& Zhang, Bin. 2013. A Novel Ant Colony Optimization Algorithm for Large Scale QoS-Based Service Selection Problem. Discrete Dynamics in Nature and Society،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-500287
Modern Language Association (MLA)
Zhang, Changsheng…[et al.]. A Novel Ant Colony Optimization Algorithm for Large Scale QoS-Based Service Selection Problem. Discrete Dynamics in Nature and Society No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-500287
American Medical Association (AMA)
Zhang, Changsheng& Yin, Hao& Zhang, Bin. A Novel Ant Colony Optimization Algorithm for Large Scale QoS-Based Service Selection Problem. Discrete Dynamics in Nature and Society. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-500287
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-500287