基于遗传算法负载均衡的网格工作流技术研究

Research on Grid Workflow Technology of Load Balancing Based on Grenetic Algorithm

针对传统的网格工作流系统中,在分配任务的过程中,根据执行任务的最短时间选取传输路径,这样造成多条路径负载的不均衡,导致网格工作流的工作效率低的问题。文章提出一种基于遗传算法负载均衡的网格工作流算法。通过模拟自然界的生物进化过程对任务空间进行随机化搜索,根据预定任务的适应度函数,并用全局并行搜索方式找到最优节点,避免了传统均衡方法的逐次匹配执行带来的低效问题。实验表明,该新算法能够实现快速负载均衡,提高网格工作流系统的工作效率,取得令人满意的结果。

In traditional grid workflow system,in assigned process,according to the shortest time selecting mission transmission path,so causing multiple paths load of unbalanced,causing grid workflow work the problem of low efficiency.This paper presents a genetic algorithm-based load balancing algorithm for grid work flow.By simulating the natural process of biological evolution were randomized to the task of the search space,according to the fitness function of scheduled tasks,and parallel with the global search for ways to find the best node,method is to avoid the traditional balance of the implementation of successive matching problems caused by inefficient.Experimental results show that the new algorithm is fast load balancing,grid workflow system to improve the work efficiency,and achieved satisfactory results.