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一种基于蚁群算法动态均衡的网格任务调度 被引量:1

A Grid Task Scheduling with Dynamic Equilibrium Based on Ant Colony Algorithm
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摘要 网格资源分配属于NP-难问题,为了更好地解决该问题,首先建立一种性能QoS优化的作业级网格任务调度模型和目标函数,并对资源和任务数进行了分析.提出了基于动态信誉度的改进蚁群算法RACO(reputation-based ACO)进行网格任务调度,RACO引入空间效率和时间效率的动态调节因子,同时采用局部和全局信息素更新策略.仿真实验表明,RACO在资源利用率、动态均衡方面优于Min-min,Max-min和ACO算法. Resource allocation in grid is an NP-hard problem.To optimize the grid system,a performance QoS optimization model is developed for grid task scheduling and objective function,with the number of resources and tasks analyzed in detail.Then,an improved ant colony algorithm named RACO(reputation-based ant colony algorithm) is presented to schedule tasks in grid,based on the dynamic reputation.Introducing a dynamic scheduling factor involving both space and time efficiencies,a local and global pheromone updating strategy is applied to RACO.Simulation results showed that RACO algorithm outperforms the conventional Min-min,Max-min and ACO in resource utilization rate and dynamic equilibrium.
出处 《东北大学学报(自然科学版)》 EI CAS CSCD 北大核心 2010年第5期630-633,共4页 Journal of Northeastern University(Natural Science)
基金 国家自然科学基金资助项目(60673159 70671020) 国家高技术研究发展计划项目(2007AA041201) 教育部科学技术研究发展计划项目(108040) 高等学校博士学科点专项科研基金资助项目(20060145012 20070145017)
关键词 网格计算 任务调度 动态均衡 蚁群算法 信誉 grid compution task scheduling dynamic equilibrium ant colony algorithm reputation
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参考文献10

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共引文献1

同被引文献9

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  • 8王永贵,韩瑞莲.基于改进蚁群算法的云环境任务调度研究[J].计算机测量与控制,2011,19(5):1203-1204. 被引量:46
  • 9王磊,夏阳,史强,文艾.网格环境下基于QoS的协作型任务调度算法研究[J].小型微型计算机系统,2011,32(8):1643-1646. 被引量:2

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