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Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Qiqi Zhang¹, Shaojin Geng², Xingjuan Cai^1,*

1 School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, 030024, China
2 College of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China

* Corresponding Author: Xingjuan Cai. Email:

(This article belongs to this Special Issue: Swarm Intelligence and Applications in Combinatorial Optimization)

Computer Modeling in Engineering & Sciences 2023, 135(3), 1863-1900. https://doi.org/10.32604/cmes.2023.022287

Received 02 March 2022; Accepted 03 August 2022; Issue published 23 November 2022

Abstract

Cloud computing technology is favored by users because of its strong computing power and convenient services. At the same time, scheduling performance has an extremely efficient impact on promoting carbon neutrality. Currently, scheduling research in the multi-cloud environment aims to address the challenges brought by business demands to cloud data centers during peak hours. Therefore, the scheduling problem has promising application prospects under the multi-cloud environment. This paper points out that the currently studied scheduling problems in the multi-cloud environment mainly include independent task scheduling and workflow task scheduling based on the dependencies between tasks. This paper reviews the concepts, types, objectives, advantages, challenges, and research status of task scheduling in the multi-cloud environment. Task scheduling strategies proposed in the existing related references are analyzed, discussed, and summarized, including research motivation, optimization algorithm, and related objectives. Finally, the research status of the two kinds of task scheduling is compared, and several future important research directions of multi-cloud task scheduling are proposed.

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