A survey on cloud computing scheduling algorithms

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS
M. Malekimajd, Ali Safarpoor-Dehkordi
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引用次数: 1

Abstract

Cloud computing has emerged as one of the hottest topics in technology and has quickly become a widely used information and communication technology model. Performance is a critical component in the cloud environment concerning constraints like economic, time, and hardware issues. Various characteristics and conditions for providing solutions and designing strategies must be dealt with in different situations to perform better. For example, task scheduling and resource allocation are significant challenges in cloud management. Adopting proper techniques in such conditions leads to performance improvement. This paper surveys existing scheduling algorithms concerning the macro design idea. We classify these algorithms into four main categories: deterministic algorithms, metaheuristic algorithms, learning algorithms, and algorithms based on game theory. Each category is discussed by citing appropriate studies, and the MapReduce review is addressed as an example.
云计算调度算法综述
云计算已成为当今技术领域最热门的话题之一,并迅速成为一种广泛应用的信息通信技术模式。性能是云环境中涉及经济、时间和硬件问题等约束的关键组件。提供解决方案和设计策略的各种特点和条件必须在不同的情况下处理,以便更好地执行。例如,任务调度和资源分配是云管理中的重大挑战。在这种情况下采用适当的技术可以提高性能。本文综述了基于宏设计思想的现有调度算法。我们将这些算法分为四大类:确定性算法、元启发式算法、学习算法和基于博弈论的算法。通过引用适当的研究来讨论每个类别,并以MapReduce评论为例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Multiagent and Grid Systems
Multiagent and Grid Systems COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
1.50
自引率
0.00%
发文量
13
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