为解决在异构计算环境中现有的云计算负载均衡算法存在的慢任务频繁抖动的问题,提出了一种能减低慢任务调度抖动概率的算法——DPST算法.首先通过定义一种异构计算节点中异构任务的能力度量,对执行异构任务的节点处理能力进行了归一化;然后通过引入节点能力预判机制,降低慢任务无效调度的次数；并且利用慢任务和慢节点双队列机制,提高了调度效率.实验结果表明,DPST相对于Hadoop平台在异构环境下任务调度的抖动次数下降了40％以上.由于有效降低了任务调度的抖动次数,在异构环境中DPST算法能明显地缩短任务的平均响应时间并提高系统的吞吐量.%With regard to the thrashing problem of load-balancing algorithm in heterogeneous environments, a new scheduling algorithm called Dynamic Predetermination of Slow Task ( DPST) was designed to reduce the probability in slow task scheduling and improve load-balancing. Through defining capability measure of heterogeneous task in heterogeneous nodes, the capacity of nodes which performed heterogeneous tasks was normalized. With the introduction of predetermination, thrashing result from heterogeneous environments was reduced. By using double queues of slow task and slow node, the efficiency of scheduling was improved. The experimental results show that the thrashing times in heterogeneous environments fell by more than 40% compared with Hadoop. Because thrashing times have been reduced effectively, DPST algorithm has better performance in reducing average response time and increasing system throughput in heterogeneous environments.
展开▼
