Bi-direction Adjust Heuristic for Workflow Scheduling in Clouds

Zhicheng Cai, Xiaoping Li, Long Chen, J. Gupta
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引用次数: 9

Abstract

This paper considers the workflow scheduling problem in Clouds with the hourly charging model and data transfer times. It deals with the allocation of tasks to suitable VM instances while maintaining the precedence constraints on one hand and meeting the workflow deadline on the other. A bi-direction adjust heuristic (BDA) is proposed for the considered problem. Matching of tasks and the VM types is modeled as Mixed Integer Linear programming (MILP) problem and solved using CPLEX at the first stage of BDA. In the second stage, forward and backward scheduling procedures are applied to allocate tasks to VM instances according to the result of the first stage. In the backward scheduling procedure, a priority rule considering the finish time, wasted time fractions and added hours is developed to make appropriate matches of tasks and free time slots. Extensive experimental results show that the proposed BDA heuristic outperforms the existing state-of-the-art heuristic ICPCP in all cases. Further, compared with ICPCP, about 80% percentage of VM renting cost is saved for instances with 900 tasks at most.
云环境下工作流调度的双向调整启发式算法
本文考虑了基于小时计费模型和数据传输次数的云中工作流调度问题。它处理任务分配到合适的VM实例,同时一方面保持优先级约束,另一方面满足工作流截止日期。针对该问题,提出了一种双向调整启发式算法(BDA)。将任务与虚拟机类型的匹配建模为混合整数线性规划(MILP)问题,并在BDA的第一阶段使用CPLEX进行求解。在第二阶段,根据第一阶段的结果,应用正向和向后调度过程,将任务分配给虚拟机实例。在逆向调度过程中,提出了考虑完成时间、浪费时间和增加时间的优先级规则,以使任务和空闲时段进行适当匹配。大量的实验结果表明,所提出的BDA启发式算法在所有情况下都优于现有的最先进的启发式ICPCP算法。此外,与ICPCP相比,对于最多有900个任务的实例,可以节省约80%的VM租用成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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