Dynamic Service Selection Based on Ant Colony System

Ying Li; Wei Qin Tong; Xiao Li Zhi; D. Ding

doi:10.4028/www.scientific.net/AMM.182-183.2136

Paper Titles

A Genetic Algorithm with Weight-Based Encoding for One-Dimensional Bin Packing Problem
p.2100

An Anti-Eavesdropping Network Coding Algorithm
p.2105

A Multi-Strategy Word Sense Disambiguation Method
p.2109

The Gray Processing of Moon Digital Orthophoto Map
p.2113

A Hybrid Ant Algorithm for the Vehicle Routing Problem
p.2118

A Maintenance Strategy of Materialized Views in Distributed Environment
p.2123

The Research of MapReduce on the Cloud Computing
p.2127

Study on Filter Algorithm of QoS-Based Fuzzy Multi-Attribute Web Service Composition
p.2131

Dynamic Service Selection Based on Ant Colony System
p.2136

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183Dynamic Service Selection Based on Ant Colony...

Dynamic Service Selection Based on Ant Colony System

Abstract:

In this paper,ant colony system(ACS)is applied to the dynamic service selection.We design the novel pheromone update rule and the path length between the service node is generated by the QoS parameters of the services. The optimal path in ACS is correspond to a set of optimal QoS parameters composition of services. When the QoS parameters of services are changed, the parameters of ACS will be changed automatically during the process of finding the shortest path. That will improve the reliability of the service selection.

You might also be interested in these eBooks

Applied Mechanics and Mechatronics Automation

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

2136-2141

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.2136

Citation:

Cite this paper

Online since:

June 2012

Authors:

Ying Li, Wei Qin Tong, Xiao Li Zhi, D. Ding

Keywords:

Colony System (ACS), Parameter, QoS, Service Selection

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Carey M, Johnson D. Computers and Intractability: A Guide to the Theory of NP-Completeness [M]. NewYork: W.H. Freeman and Company, (2005).

Google Scholar

[2] SGoss S Aron, J L Deneubourg, J M Pasteels. Self-organized shortcuts in the Argentine ant[J]. Naturwissen-chafien, 1989, 76 : 579 - 581.

DOI: 10.1007/bf00462870

Google Scholar

[3] Coloni A, Dorigo M, Maniezzo V, et al. Distributed Optimization by Ant Colonies[C] Proceedings of European Conference on Artificial Life. Paris, France1991, 134-142.

Google Scholar

[4] WANG Yong, DAI Gui-ping, JIANG Zheng-tao et al. A Trust Enhanced Service Composition Scheduling Algorithm [J]. Acta Electronica Sinica, 37(10): 2234-2238, (2009).

Google Scholar

[5] Li Shiyong, Chen yongqiang, Li yan. The ant algorithm and application. Harbin Institute of Technology, (2004).

Google Scholar

[6] Dorigo M, Stutzle T. Ant colony optimization. Cambridge, MA: MIT Press, (2003).

Google Scholar

[7] Chu S C, Roddick J F, Pan J S, et al. Parallel ant colony systems. Lecture Notes in Artificial Intelligence, 2003, 28(17): 279-284.

Google Scholar

[8] Duan HaiBin, Wang DaoBo, Yu XiuFen. ACA hardware implementation research [J]. Control and Decision, 2007, 22(3): 241-246.

Google Scholar

[9] Wang Yong, Dai Gui-Ping, Hou Ya-Rong. Dynamic Methods of Trust-Aware Composite Service Selection [J]. Chinese Journal of Computers, 32(8): 1668-1675, (2009).

Google Scholar

[10] Peng xiao-ming, He Yan-xiang, Zhu Bing-jian. Application of Ant Colony Algorithm in Web Services Composition [J]. Computer Engineering, 35(10): 182-187, (2009).

Google Scholar