云环境下一种基于任务类型匹配的负载均衡策略研究

针对云计算环境下大量并行计算节点容易产生计算节点之间的负载不均问题,本文提出了一种基于任务类型匹配的负载均衡方案。该方案针对任务集中的多种不同长度的子任务类型情况进行判定,并对当前主流的Max-Min和Min-Min两种启发式负载均衡算法进行分析,综合其优缺点,并针对任务集的类型采用不同的算法进行任务调度。实验结果表明在该负载均衡的策略下,提出的方案具有比单一应用Max-Min或者Min-Min算法具有更好的负载均衡特性和更短的完成时间。

A Load Balancing Strategy Based On Task Type Matching For Cloud Computing Environment

For a large number of parallel computing nodes under the cloud computing environment, It is easy to produce uneven load between computing nodes, this paper proposes a load balancing scheme based on task type matching. This proposal is focus on the different lengths of the subtasks of a task set and to determine the task set type, we analyzed the two popular heuristic algorithms named Max-Min and Min-Min and compared their advantages and disadvantages, then use different algorithm for task scheduling according to the type of the task set.The experimental results show that the proposed solution has better load balancing features and a shorter completion time than we only use the one algorithm of Max-Min and Min-Min.