改进蚁群算法的云存储任务调度算法研究  

Research on Task Schedule Algorithm of Cloud Storage Based on Improved Ant Colony Algorithm

作　　者：袁恩隆 李飞[1] 唐籍涛[1] 赵伯听[1] 

机构地区：[1]成都信息工程学院网络工程学院,成都610225

出　　处：《四川理工学院学报（自然科学版）》2014年第1期41-44,共4页Journal of Sichuan University of Science & Engineering(Natural Science Edition)

基　　金：四川省科技支撑项目(2011GZ0195)

摘　　要：由于云存储环境与云计算环境中不同,若直接将云计算环境中的任务调度算法移植到云存储环境中,必然会导致任务调度的效率下降。为解决此问题,提出了一种适用于云存储环境中的改进蚁群算法。改进蚁群算法能使云计算环境的任务调度算法更符合云存储的环境;同时,对于改进PSO算法在引入存在矩阵时,由于数据资源不存在而造成算法前期优化浪费引起效率低下的问题进行了有效解决。分析测试结果表明,提出的改进蚁群算法在云存储环境的任务调度算法在保障有效解的前提下能够拥有更快的收敛速度。Due to the different between the cloud storage environment and the cloud computing environment, directly transplanting task scheduling which used in cloud computing to the cloud storage environment will inevitably lead to a decline in the efficiency of task scheduling. To solve this problem, an improved ant colony algorithm which is applicable to cloud storage environment is proposed. This improved ant colony algorithm is more suitable for cloud storage environment. At the same time, there is no data resources when the improved PSO algorithm is introduced in matrix, so that a waste of early opti- mizing of the algorithm is produced, which causes a problem that the efficiency is very low, the problem is solved effectively. Analysis of test results shows that the improved ant colony algorithm propsed in the clord storage environment task scheduling algorithm has faster convergence rate under the premise to guarantee efficient solutions.

关 键 词：云存储 任务调度 蚁群算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]