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Unified Multi-constraint and Multi-objective Workflow Scheduling for Cloud System

机译:云系统的统一多约束多目标工作流调度

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With the development of cloud computing, the problem of scheduling workflow in cloud system attracts a large amount of attention. In general, the cloud workflow scheduling problem requires to consider a variety of optimization objectives with some constraints. Traditional workflow scheduling methods focus on single optimization goal like makespan and single constraint like deadline or budget. In this paper, we first make a unified formalization of the optimality problem of multi-constraint and multi-objective cloud workflow scheduling using pareto optimality theory. We also present a two-constraint and two-objective case study, considering deadline, budget constraints and energy consumption, reliability objectives. A general list scheduling algorithm and a tuning mechanism are designed to solve this problem. Through extensive experimental, it confirms the efficiency of the unified multi-constraint and multi-objective cloud workflow scheduling system.
机译:随着云计算的发展,云系统中的工作流调度问题引起了人们的广泛关注。通常,云工作流调度问题需要考虑各种具有某些约束的优化目标。传统的工作流调度方法侧重于单个优化目标(例如制造期限)和单个约束(例如截止日期或预算)。在本文中,我们首先使用Pareto最优性理论对多约束和多目标云工作流调度的最优性问题进行统一形式化。我们还提出了两个约束和两个目标的案例研究,其中考虑了截止日期,预算约束和能耗,可靠性目标。设计了一种通用的列表调度算法和一种调整机制来解决此问题。通过广泛的实验,确定了统一的多约束多目标云工作流调度系统的效率。

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