基于MVO算法的云计算多目标、基于信任的工作流调度方法

F. Ebadifard, S. M. Babamir, Fatemeh Labafiyan
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引用次数: 1

摘要

虚拟机上的任务调度问题是为任务选择合适的资源,使其关联的任务已经执行。由于工作流包含一组任务,因此失败的可能性随着整个工作流中任务的失败而增加。将任务分配到可靠性更高的虚拟机上,可以提高工作流调度效率。因此,信任关系是资源分配和作业调度的一个重要因素,本文提出了一种估算工作流程所在虚拟机信任的好方法。除了信任是工作流调度的一个重要因素之外,还有其他衡量服务提供者和客户满意度的标准。通过增加请求数、虚拟机的多样性以及目标之间的矛盾,使得寻找最优Pareto front更具挑战性。因此,多目标进化算法需要面对较大的排列空间来寻找目标的最优权衡。本文提出了一种基于MVO算法的多目标工作流调度算法,以提高算法的多样性和收敛性,使该算法能够同时考虑服务提供商和客户的QoS需求。
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A Multi Objective & Trust-Based Workflow Scheduling Method in Cloud Computing based on the MVO Algorithm
The problem of task scheduling on VMs is selecting appropriate resources for a task so that its associated tasks have already been executed. Since the workflow contains a set of tasks, the likelihood of failure increases with the failure of a task throughout the workflow. The allocation of tasks on virtual machines with higher reliability improves workflow-scheduling efficiency. Therefore, Trust relationship is an important factor of resource allocation and job scheduling, and in this paper, we have presented a good method to estimate the trust of virtual machines on which the workflow is run. In addition to the trust, which is an important factor in the workflow scheduling, there are other criteria for the satisfaction of service providers and customers. By increasing the number of requests and the diversity of virtual machines as well as the contradiction between objectives, finding the optimal Pareto front is more challenging. Therefore, multi-objective evolutionary algorithms face a large space of permutations to find an optimal tradeoff of objectives. In this paper, we present a multi-objective workflow-scheduling algorithm using MVO algorithm with the aim of increasing diversity and convergence, so that the proposed method can consider QoS requirements for service providers and customers simultaneously.
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