Cloud Computing Resource Scheduling Based on Improved Ant Colony Algorithm and Particle Swarm Algorithm
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    Abstract:

    Aiming at uneven resource distribution in cloud computing and bad distribution effect, this paper distributes resources in improved and colony algorithm and particle swarm algorithm. First of all, improve the inertia weight value of particle swarm algorithm, set the fitness function and select particles at the optimal location, then convert the location of selected particles into the value of ant colony algorithm's initial pheromone and improve ant colony algorithm's selection of pheromone through wolves algorithm. Through simulation experiment, compared with ant colony algorithm and particle swarm algorithm, algorithm in this paper has been significantly improved in time to complete tasks and energy consumption.

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单好民.基于改进蚁群算法和粒子群算法的云计算资源调度.计算机系统应用,2017,26(6):187-192

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History
  • Received:October 23,2016
  • Revised:December 19,2016
  • Online: June 08,2017
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