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An optimization algorithm for multipath parallel allocation for service resource in the simulation task workflow.

Zhiteng Wang1, Hongjun Zhang1, Rui Zhang1

  • 1PLA University of Science & Technology, Nanjing 210007, China.

Thescientificworldjournal
|June 26, 2014
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Summary
This summary is machine-generated.

This study introduces an optimization algorithm for multipath service resource parallel allocation to enhance simulation task success. The proposed method improves the probability of success and timeliness in military modeling and simulation workflows.

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Area of Science:

  • Computer Science
  • Engineering
  • Operations Research

Background:

  • Service-oriented modeling and simulation (SOMS) requires efficient service resource allocation during task execution.
  • Optimizing resource allocation is crucial for effective task completion, especially in demanding fields like military simulations.
  • Improving the probability of success and timeliness of simulation task workflows is a key challenge.

Purpose of the Study:

  • To propose an optimization algorithm for multipath service resource parallel allocation.
  • To enhance the effectiveness of service resource allocation in simulation task workflows.
  • To improve the probability of success and timeliness in military modeling and simulation.

Main Methods:

  • Development of a multipath service resource parallel allocation model.
  • Application of a multiple chains coding scheme quantum optimization algorithm for efficient search.
  • Extension of the parallel search space to boost search efficiency.

Main Results:

  • Simulation experiments evaluated the impact of the optimization algorithm, allocation strategy, and path number.
  • The proposed algorithm demonstrated effectiveness in improving the probability of success for simulation task workflows.
  • Timeliness of simulation task workflows was also significantly enhanced by the optimization approach.

Conclusions:

  • The developed optimization algorithm for multipath service resource parallel allocation is effective.
  • The method successfully improves both the probability of success and timeliness in simulation task workflows.
  • This approach offers a valuable solution for resource allocation challenges in service-oriented modeling and simulation, particularly in military applications.