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HEART : Unrelated parallel machines problem with precedence constraints for task scheduling in cloud computing using heuristic and meta‐heuristic algorithms
Software: Practice and Experience ( IF 3.5 ) Pub Date : 2020-09-07 , DOI: 10.1002/spe.2890
Amit Kumar Bhardwaj 1, 2 , Yuvraj Gajpal 2 , Chirag Surti 3 , Sukhpal Singh Gill 4
Affiliation  

Cloud computing is becoming a profitable technology because of it offers cost‐effective IT solutions globally. A well‐designed task scheduling algorithm ensures the optimal utilization of clouds resources and reducing execution time dynamically. This research article deals with the task scheduling of inter‐dependent subtasks on unrelated parallel computing machines in a cloud computing environment. This article considers two variants of the problem‐based on two different objective function values. The first variant considers the minimization of the total completion time objective function while the second variant considers the minimization of the makespan objective function. Heuristic and meta‐heuristic (HEART) based algorithms are proposed to solve the task scheduling problems. These algorithms utilize the property of list scheduling algorithm of unrelated parallel machine scheduling problem. A mixed integer linear programming (MILP) formulation has been provided for the two variants of the problem. The optimal solution is obtained by solving MILP formulation using A Mathematical Programming Language (AMPL) software. Extensive numerical experiments have been performed to evaluate the performance of proposed algorithms. The solutions obtained by the proposed algorithms are found to out‐perform the existing algorithms. The proposed algorithms can be used by cloud computing service providers (CCSPs) for enhancing their resources utilization to reduce their operating cost.

中文翻译:

HEART:使用启发式和元启发式算法的云计算任务调度中具有优先约束的不相关并行机问题

云计算正在成为一项有利可图的技术,因为它在全球范围内提供具有成本效益的 IT 解决方案。精心设计的任务调度算法可确保云资源的最佳利用并动态减少执行时间。这篇研究文章涉及云计算环境中不相关的并行计算机上相互依赖的子任务的任务调度。本文考虑了该问题的两种变体——基于两个不同的目标函数值。第一个变体考虑总完成时间目标函数的最小化,而第二个变体考虑 makespan 目标函数的最小化。提出了基于启发式和元启发式(HEART)的算法来解决任务调度问题。这些算法利用了无关并行机调度问题的列表调度算法的特性。已为该问题的两个变体提供了混合整数线性规划 (MILP) 公式。最优解是通过使用数学编程语言 (AMPL) 软件求解 MILP 公式获得的。已经进行了大量的数值实验来评估所提出算法的性能。发现由所提出的算法获得的解决方案优于现有算法。云计算服务提供商(CCSP)可以使用所提出的算法来提高他们的资源利用率,从而降低他们的运营成本。最优解是通过使用数学编程语言 (AMPL) 软件求解 MILP 公式获得的。已经进行了大量的数值实验来评估所提出算法的性能。发现由所提出的算法获得的解决方案优于现有算法。云计算服务提供商(CCSP)可以使用所提出的算法来提高他们的资源利用率,从而降低他们的运营成本。最优解是通过使用数学编程语言 (AMPL) 软件求解 MILP 公式获得的。已经进行了大量的数值实验来评估所提出算法的性能。发现由所提出的算法获得的解决方案优于现有算法。云计算服务提供商(CCSP)可以使用所提出的算法来提高他们的资源利用率,从而降低他们的运营成本。
更新日期:2020-09-07
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