基于自适应塔斯马尼亚魔鬼优化算法的高效任务调度,适用于云计算环境中的大数据应用

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ashis Kumar Mishra, Subasis Mohapatra, Pradip Kumar Sahu
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引用次数: 0

摘要

云计算中最困难的问题之一是在云上的适当资源上调度任务。这一点非常重要,因为多个任务可能需要在不同的虚拟机上有效调度,以最大限度地提高资源利用率,最小化时间跨度。因此,人们一直在努力使用元启发式算法来解决任务调度问题。然而,这些技术偶尔会出现早期收敛并陷入局部搜索。为解决这些问题,本研究提出了一种基于多目标的云计算大数据应用任务调度方法。为实现这一目标,本研究创建了自适应塔斯马尼亚魔鬼优化(ATDO)方法,重点解决具有挑战性的优化问题。随后,基于对立面的学习技术(OBL)与 TDO 相结合,以保持种群的多样性,提高对理想答案的收敛性。此外,在设计多目标函数(MOF)时,还考虑了成本、工期和资源利用率。所提出的策略包括高效的解决方案表示、高效的适应度函数推导、TDO 和 OBL 算子。所提出的方法在调度 1000 个任务和 20.97 度不平衡时耗时最少,为 2134 毫秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Adaptive Tasmanian Devil Optimization algorithm based efficient task scheduling for big data application in a cloud computing environment

Adaptive Tasmanian Devil Optimization algorithm based efficient task scheduling for big data application in a cloud computing environment

One of the most difficult issues in cloud computing is scheduling tasks on appropriate resources on the cloud.This is significant because multiple tasks may need to be efficiently scheduled across different virtual machines to maximize resource utilization and minimize makespan. As a result, various efforts have been made to use metaheuristic algorithms to tackle the task scheduling problem. However, these techniques may occasionally experience early convergence and be trapped in local search. This research proposes a multi-objective-based task scheduling in cloud computing for big data applications to address these issues. To accomplish this goal, the adaptive Tasmanian Devil Optimization (ATDO) method is created in this study, with a focus on resolving challenging optimization issues. Following that, the opposition-based learning technique (OBL) is combined with TDO to maintain the population diversity and improve convergence on the ideal answer. In addition, cost, makespan,and resource utilization are taken into account when designing the multi-objective function (MOF). The proposed strategy included efficient solution representation, efficient fitness function derivation, TDO, and OBL operators. The effectiveness of the strategy is examined using several evaluation metrics, and its efficacy is compared with those of other approaches.The proposed method takes a minimum time of 2134 ms for scheduling 1000 tasks and 20.97 degree of imbalance.

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来源期刊
Multimedia Tools and Applications
Multimedia Tools and Applications 工程技术-工程:电子与电气
CiteScore
7.20
自引率
16.70%
发文量
2439
审稿时长
9.2 months
期刊介绍: Multimedia Tools and Applications publishes original research articles on multimedia development and system support tools as well as case studies of multimedia applications. It also features experimental and survey articles. The journal is intended for academics, practitioners, scientists and engineers who are involved in multimedia system research, design and applications. All papers are peer reviewed. Specific areas of interest include: - Multimedia Tools: - Multimedia Applications: - Prototype multimedia systems and platforms
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