基于不确定性理论的多维资源调度方法  

Multi-dimensional Resource Scheduling Method Based on Uncertainty Theory

作　　者：刘丰年 LIU Feng-nian(College of Applied Engineering,Henan University of Science and Technology,Sanmenxia 472000,China;Sanmenxia Polytechnic,Sanmenxia 472000,China)

机构地区：[1]河南科技大学应用工程学院,三门峡472000 [2]三门峡职业技术学院,三门峡472000

出　　处：《北京服装学院学报（自然科学版）》2020年第3期49-54,共6页Journal of Beijing Institute of Fashion Technology：Natural Science Edition

基　　金：河南省高等学校重点科研项目(17A413010);河南省科技攻关项目(182102210479)。

摘　　要：针对云环境多维资源分配过程中延迟过大问题,提出了一种基于不确定性理论的多维资源调度方法。首先,设计了基于直觉模糊推理的资源调度算法,提升了云基础设施中的资源调度效率;其次,设计了多维资源负载优化算法,实现云基础设施中调度资源的负载均衡,避免了资源不足和过度利用,优化了每类请求的延迟时间。基于Cloudsim平台在云数据中心对所提出的方法和现有的代表性方法进行了仿真和比较,结果表明本文提出的方法在成功率、资源调度效率和响应时间方面均具有更优越的性能。A multi-dimensional resource scheduling method based on uncertainty theory was proposed to solve the problem of large delay in multi-dimensional resource allocation in cloud environment.Firstly,a resource scheduling algorithm based on intuitionistic fuzziness was designed to improve the efficiency of resource scheduling in cloud infrastructure.Secondly,a multi-dimensional resource load optimization algorithm was designed to realize load balancing of scheduling resources in cloud infrastructure,avoiding resource shortage and over utilization and optimizing the request delay of each type.Thirdly,simulation and comparison were made between this method and the existing representative methods based on Cloudsim platform in cloud data center.The results show that this method has better performance in success rate,resource scheduling efficiency and response time.

关 键 词：资源调度 直觉模糊推理 负载均衡 平均延时 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]