Task scheduling techniques in cloud computing: A literature survey

Cloud computing manages a variety of virtualized resources, which makes scheduling a critical component. In the cloud, a client may utilize several thousand virtualized assets for every task. Consequently, manual scheduling is not a feasible solution. The basic idea behind task scheduling is to slat...

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Vydané v:Future generation computer systems Ročník 91; s. 407 - 415
Hlavní autori: Arunarani, AR, Manjula, D., Sugumaran, Vijayan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.02.2019
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ISSN:0167-739X, 1872-7115
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Shrnutí:Cloud computing manages a variety of virtualized resources, which makes scheduling a critical component. In the cloud, a client may utilize several thousand virtualized assets for every task. Consequently, manual scheduling is not a feasible solution. The basic idea behind task scheduling is to slate tasks to minimize time loss and maximize performance. Several research efforts have examined task scheduling in the past. This paper presents a comprehensive survey of task scheduling strategies and the associated metrics suitable for cloud computing environments. It discusses the various issues related to scheduling methodologies and the limitations to overcome. Distinctive scheduling procedures are studied to discover which characteristics are to be included in a given system and which ones to disregard. The literature survey is organized based on three different perspectives: methods, applications, and parameter-based measures utilized. In addition, future research issues related to cloud computing-based scheduling are identified. •Presents a comprehensive survey of task scheduling strategies and the associated metrics suitable for cloud computing environments.•Discusses the various issues related to scheduling methodologies and the limitations to overcome.•Distinctive scheduling procedures are studied to discover which characteristics are to be included in a given system and which ones to disregard.•Literature survey organized based on three different perspectives: methods, applications, and parameter-based measures utilized.•Future research issues related to cloud computing-based scheduling identified.
ISSN:0167-739X
1872-7115
DOI:10.1016/j.future.2018.09.014