云计算环境下任务调度算法的研究  

Research on Task Scheduling Algorithm In Cloud Computing Environment

作　　者：李菡薏 陈家琪[1] 

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《电子科技》2015年第11期43-46,60,共5页Electronic Science and Technology

基　　金：上海市教委科研创新基金资助项目(12zz146)

摘　　要：在云计算环境中存在庞大的任务数,为了能更加高效地完成任务请求,如何进行有效地任务调度是云计算环境下实现按需分配资源的关键。针对调度问题提出了一种基于蚁群优化的任务调度算法,该算法能适应云计算环境下的动态特性,且集成了蚁群算法在处理NP-Hard问题时的优点。该算法旨在减少任务调度完成时间。通过在Cloud Sim平台进行仿真实验,实验结果表明,改进后的算法能减少任务平均完成时间、并能在云计算环境下有效提高调度效率。There are large number of tasks in cloud computing environment, and how to conduct effective task scheduling is the key to allocate resources by need in cloud computing environment in order to be more efficient com- pletion of task request. This paper proposes a task scheduling algorithm based on the ant colony optimization which an adapt to the dynamic characteristics of the cloud computing environment coupled with the advantages of ant colony optimization in the treatment of NP-Hard. The algorithm is designed to minimize task completion time during schedu- ling. Simulation on the CloudSim platform shows that this algorithm can effectively improve the task scheduling time under cloud computing environment.

关 键 词：云计算 任务调度 蚁群算法 

分 类 号：N301.6[自然科学总论]