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贾 嘉,慕德俊. 基于人工蜂群的云计算负载均衡算法[J]. 科学技术与工程, 2020, 20(16): 6532-6537.
JIA Jia.Load balancing in Cloud Computing by Artificial Bee Colony algorithm[J].Science Technology and Engineering,2020,20(16):6532-6537.
基于人工蜂群的云计算负载均衡算法
Load balancing in Cloud Computing by Artificial Bee Colony algorithm
投稿时间:2019-11-04  修订日期:2020-03-09
DOI:
中文关键词:  云计算  人工蜂群 负载均衡  最大完工时间 反应时间  不平衡度 任务迁移次数
英文关键词:cloud  computing artificial  bee colony  load balancing  make span  response time  imbalance degree  number of  task migration
基金项目:国家重点研发计划项目(编号:2016YFB0301203)
     
作者单位
贾 嘉 西北工业大学自动化学院
慕德俊 网络空间安全学院
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中文摘要:
      针对云计算负载均衡问题,基于人工蜂群的思想设计负载均衡算法。首先建立了云计算系统中计算负载的数学模型;在此模型基础上,分三步实现负载均衡。一、负载均衡决策,计算云系统整体的负载,在云系统整体上尚未过载且负载不均衡的前提下,启动后续步骤。二、虚拟机分组,将云系统中的全体虚拟机分别归入过载、低负载、负载均衡三个分组。后续步骤中需要被迁移的计算任务通常处在过载虚拟机之上,而迁移目的地通常是一个低负载虚拟机。三、计算任务调度,将过载虚拟机上的任务向外迁移,并设计规则来选择恰当的低负载虚拟机作为迁移目的地。实验验证了所提算法的有效性。
英文摘要:
      A load-balancing algorithm was designed based on the idea of artificial bee colony for cloud computing. Firstly, the mathematical model of computing load in cloud computing system was established; based on this model, load balancing was implemented in three steps. First, the overall load was calculated. In the premise that the cloud system not overloaded and the loads were imbalanced, subsequent steps were initiated. Second, we group all virtual machines in the cloud system into three groups: overload, low load, and load balancing. The computing tasked that need to be migrated in the subsequent steps were usually on an overloaded virtual machine, and the migration destination was usually a low-loaded virtual machine. Third, we choose tasks from overloaded virtual machines to migrate. Subsequently, we designed rules to select the appropriate low-load virtual machine as the migration destination. The experiment verified the effectiveness of the proposed algorithm.
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