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引用次数: 0
摘要
从解决复杂的计算问题到解决庞大的数据密集型任务,云计算作为一种新兴的技术而出现。它不局限于提出巨大的问题,而且还满足有不同需求的日常客户。为了实现如此多样化的用户,Cloud总是需要一个有效的任务调度来满足这种动态。因此,本文提出了一种基于Batch Mode Heuristic for Cloud Environment (ETSBMH)的高效任务调度技术,该技术以一种有效的方式映射小云以减少makespan,并提供了一种描述异构虚拟机完成时间变化的新度量。我们将其命名为机器完工时间感知完成时间变化(MMACV),它考虑了机器之间相对于完工时间的完工时间变化。结果表明,该方法在缩短完工时间、减少MMACV和提高平均机器利用率方面是有效的。
Efficient Task Scheduling Technique under Batch Mode Heuristic for Cloud Environment
From solving complex computational problems to huge data intensive tasks, Cloud Computing is emerged as one the growing technology. It is not restricted to hand out gigantic problems but also gratifying day to day clients with variable requirements. To accomplish such a variety of users, Cloud always required an efficient task scheduling to cater such dynamism. So, this paper presents a scheduling technique named Efficient Task Scheduling technique under Batch Mode Heuristic for Cloud Environment (ETSBMH) that mapped cloudlets in an efficient way to reduce the makespan along with a new type of metric that depicts variation among heterogeneous virtual machines completion time. We named it Machine Makespan Aware Completion time Variation (MMACV) that considered completion time variation among machines with respect to makespan. Results reveal the effectiveness of proposed technique from on hand approaches in terms of reduced makespan, less MMACV and improved average machine utilization rate.