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Multiobjective noncooperative game model for cost‐based task scheduling in cloud computing
Author(s) -
Gao Ziyan,
Wang Yong,
Gao Yifan,
Ren Xingtian
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5570
Subject(s) - cloud computing , computer science , distributed computing , scheduling (production processes) , dynamic priority scheduling , job shop scheduling , two level scheduling , task (project management) , fair share scheduling , mathematical optimization , operating system , quality of service , computer network , mathematics , schedule , management , economics
Summary Task scheduling is an important issue in Cloud Computing. Cloud Computing often covers a range of different kinds of nodes, which offers a complex environment. To handle this complexity, as while as to process task scheduling in different scenarios of Cloud Computing, many algorithms have been studied. In this paper, we propose a game theory–based algorithm to the Cloud Computing task scheduling problem on the principle of minimizing the cost in the Cloud Computing. The Cloud Computing task scheduling problem is treated as a noncooperative game. The experiment results demonstrate that the game‐based algorithm has a desirable capability to reduce the cost in the Cloud Computing.