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The Scientific World Journal
Volume 2014 (2014), Article ID 507517, 11 pages
http://dx.doi.org/10.1155/2014/507517
Research Article

An Optimization Algorithm for Multipath Parallel Allocation for Service Resource in the Simulation Task Workflow

1PLA University of Science & Technology, Nanjing 210007, China
2Nanjing Artillery Academy, Nanjing 210110, China

Received 9 October 2013; Accepted 25 November 2013; Published 12 May 2014

Academic Editors: W. Sun, G. Zhang, and J. Zhou

Copyright © 2014 Zhiteng Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Service oriented modeling and simulation are hot issues in the field of modeling and simulation, and there is need to call service resources when simulation task workflow is running. How to optimize the service resource allocation to ensure that the task is complete effectively is an important issue in this area. In military modeling and simulation field, it is important to improve the probability of success and timeliness in simulation task workflow. Therefore, this paper proposes an optimization algorithm for multipath service resource parallel allocation, in which multipath service resource parallel allocation model is built and multiple chains coding scheme quantum optimization algorithm is used for optimization and solution. The multiple chains coding scheme quantum optimization algorithm is to extend parallel search space to improve search efficiency. Through the simulation experiment, this paper investigates the effect for the probability of success in simulation task workflow from different optimization algorithm, service allocation strategy, and path number, and the simulation result shows that the optimization algorithm for multipath service resource parallel allocation is an effective method to improve the probability of success and timeliness in simulation task workflow.