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基于改进蚁群优化算法的云计算调度方法 被引量:7

Cloud Computing Scheduling Method Based on Improved Ant Colony Optimization Algorithm
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摘要 云计算以其可伸缩性、高可靠性、低成本以及按需服务等诸多特点吸引了无数研究人员和企业的关注,成为了当今时代的热门话题,云计算任务调度在云计算研究领域占有十分重要的地位。论文首先分析了当前云计算任务调度现状,并对任务调度中常用的蚁群算法进行了描述,同时针对传统蚁群算法在云计算任务调度中的不足,提出了基于改进蚁群优化算法的云计算调度方法,在信息素更新和信息素挥发两个方面对蚁群算法进行了改进。最后使用CloudSim进行实验,对算法的可行性进行了分析和验证。 With the characteristics of scalability,high reliability,low cost and on-demand services etc,cloud computing has attracted the attention of numerous researchers and enterprises,and becomes a hot topic in today's era.Cloud computing task scheduling occupies a very important position in cloud computing research field.This paper first analyzes the current situation of cloud computing task scheduling,then describes the ant colony algorithm commonly used in task scheduling,and in view of the shortage of the traditional ant colony task scheduling algorithm in cloud computing,proposes cloud computing scheduling method based on improved ant colony optimization algorithm,improves the way of pheromone updating and pheromone volatilization.Finally,the experiment is carried out using CloudSim,and the feasibility of the algorithm is analyzed and verified.
作者 王恩重 陶传奇 WANG Enzhong;TAO Chuanqi(School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094;School of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 210016;Key State Laboratory for Novel Software Technology(Nanjing University),Nanjing 210023)
出处 《计算机与数字工程》 2019年第4期743-747,793,共6页 Computer & Digital Engineering
基金 国家自然科学基金(编号:61402229 61502233) 江苏省博士后基金(编号:1401043B) 南京大学软件新技术国家重点实验室开放式基金(编号:KFKT2015B10) 江苏省高校自然科学研究项目(编号:15KJB520030)资助
关键词 云计算 任务调度 蚁群优化算法 CloudSim cloud computing task scheduling ant colony optimization algorithm CloudSim
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