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面向优先级任务的移动边缘计算资源分配方法
引用本文:董思岐,吴嘉慧,李海龙,屈毓锛,胡磊.面向优先级任务的移动边缘计算资源分配方法[J].计算机工程,2020,46(3):18-23.
作者姓名:董思岐  吴嘉慧  李海龙  屈毓锛  胡磊
作者单位:火箭军工程大学作战保障学院,西安710025;中国电子科技集团公司第二十八研究所,南京210007
摘    要:目前移动边缘计算中的资源分配方法,多数按照任务请求计算卸载的时间顺序分配计算资源,未考虑实际应用中任务存在优先级的问题。针对此类情况下的计算需求,提出一种面向优先级任务的资源分配方法。根据任务平均处理价值赋予其相应的优先级,对不同优先级的任务进行计算资源加权分配,在保证高优先级任务获取充足计算资源的同时,减少完成所有任务计算的总时间及能耗,从而提高服务质量。仿真结果表明,与平均分配、按任务数据量分配和本地计算方法相比,该方法的计算时延分别降低83.76%、15.05%和99.42%,能耗分别降低84.78%、17.37%和87.69%。

关 键 词:移动边缘计算  优先级任务  加权分配  资源分配  服务质量

Resource Allocation Method for Priority Task in Mobile Edge Computing
DONG Siqi,WU Jiahui,LI Hailong,QU Yuben,HU Lei.Resource Allocation Method for Priority Task in Mobile Edge Computing[J].Computer Engineering,2020,46(3):18-23.
Authors:DONG Siqi  WU Jiahui  LI Hailong  QU Yuben  HU Lei
Affiliation:(Combat Support College,Rocket Force University of Engineering,Xi’an 710025,China;The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing 210007,China)
Abstract:In mobile edge computing,most of existing resource allocation methods allocate computing resources according to the time that tasks request computation offloading,without considering task priority in practical applications.To meet computing requirements in such cases,this paper proposes a resource allocation method for priority tasks.This method assigns priority to each task based on their average processing value,and implements weighted allocation of computing resources for tasks of different priorities.It ensures high-priority tasks obtain sufficient computing resources while the total time and energy consumption for completing all tasks are reduced.Thus the Quality of Service(QoS)is improved.Simulation results show that,compared with the method of evenly allocating computing resources,the method of allocating resources according to the amount of task data and the method of placing all tasks on mobile terminals,the calculation delay of this method is reduced by 83.76%,15.05%and 99.42%respectively,and the energy consumption is reduced by 84.78%,17.37%and 87.69%respectively.
Keywords:mobile edge computing  priority task  weighted allocation  resource allocation  Quality of Service(QoS)
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