岳璐, 傅妍芳, 钟联炯, 高武奇. 基于改进匈牙利算法的云仿真资源调度[J]. 微电子学与计算机, 2012, 29(12): 22-26.
引用本文: 岳璐, 傅妍芳, 钟联炯, 高武奇. 基于改进匈牙利算法的云仿真资源调度[J]. 微电子学与计算机, 2012, 29(12): 22-26.
YUE Lu, FU Yan-fang, ZHONG Lian-jiong, GAO Wu-qi. Cloud Simulation Resource Schedule Based on an Improved Hungary Algorithm[J]. Microelectronics & Computer, 2012, 29(12): 22-26.
Citation: YUE Lu, FU Yan-fang, ZHONG Lian-jiong, GAO Wu-qi. Cloud Simulation Resource Schedule Based on an Improved Hungary Algorithm[J]. Microelectronics & Computer, 2012, 29(12): 22-26.

基于改进匈牙利算法的云仿真资源调度

Cloud Simulation Resource Schedule Based on an Improved Hungary Algorithm

  • 摘要: 针对传统仿真系统平台的资源分配存在资源闲置、任务挤压和负载均衡等优化问题,利用云计算技术的优势研究并提出了模块化的云仿真平台框架,通过对云仿真资源调度策略研究,提出了一种改进的匈牙利算法.该算法克服了传统匈牙利算法只适用于一对一资源调度的不足,实现了多对一的仿真任务与云仿真资源分配方案,能尽量避免资源调度负载失衡.通过扩展云计算仿真平台CloudSim实现了模拟算法仿真.结果表明.该调度策略能有效的减小云环境下计算机的负载,提高了资源的利用率.

     

    Abstract: Aiming at the optimization problem of idling resource, squeezing task and loading balance in the traditional resource schedule of the cloud simulation, this paper presents cloud simulation resource scheduling strategy based on an improved Hungary algorithm.It overcomes the traditional Hungarian algorithm applies only to the lack of one-to-one resource scheduling and achieves the distribution scheme between many-to-one simulation tasks and cloud simulation resources, avoiding the resource loading balance at best.By extending the Cloud Computing platform CloudSim to test the simulation, the results show that this method can reduce the loading of computers in the cloud computing, and the resource utilization is improved too.

     

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