改进蛙跳算法的网格任务调度优化模型

为解决当前调度模型存在的局限性, 以更好完成网格环境下的任务调度目标, 结合网格任务调度的NP(Non-deterministic Polynomial)问题特点, 提出了改进蛙跳算法的网格任务调度优化模型。首先以网格任务完成时间作为调度优化指标, 然后采用蛙跳算法找到最优的网格任务调度方案, 并对蛙跳算法存在不足进行改进,以改善算法工作性能, 最后在网格仿真平台GridSim 上进行性能验证分析。实验结果表明, 改进蛙跳算法可较好完成网格任务调度, 缩短了任务完成的时间, 资源负载更加均衡, 而且性能明显要优于其他算法。

Optimization Model of Grid Task Scheduling Modified Shuffle Frog Leaping Algorithm

In order to complete task scheduling in grid environment better, and overcome the limitation of the needle current scheduling model, combined with the characteristics of grid task scheduling is a NP ( Non-deterministic Polynomial) problem, this paper proposes a novel grid task scheduling optimization model based on modified SFLA( Shuffled Frog Leaping Algorithm) . First of all, grid task completion time is taken as optimization indicators to establish mathematical model, and then leapfrog algorithm is used to find the best scheme for grid task scheduling, and leapfrog algorithm is modified to solve defect and improve the algorithm speed, the grid performance analysis were validated by GridSim. The results show that modified shuffled frog leaping algorithm can complete task scheduling, shorten the task completion time, balance the load of resources, and the performance was obviously superior to the other algorithm.