Resource Reallocation of Virtual Machine in Cloud Computing with MCDM Algorithm

被引：6

作者：

Lee, Byungjun ^{[1
]}

Oh, Kyung Hwan ^{[1
]}

Park, Hee Jung ^{[1
]}

Kim, Ung Mo ^{[1
]}

Youn, Hee Yong ^{[1
]}

机构：

[1] Sungkyunkwan Univ, Coll Informat & Commun Engn, Suwon, South Korea

来源：

2014 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC) | 2014年

关键词：

Cloud computing; Resource allocation; TOPSIS; AHP; Grey theory; Entropy; MCDM; FUZZY-SET; SELECTION; TOPSIS;

D O I：

10.1109/CyberC.2014.87

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Resource allocation for virtual machines is a crucial issue in cloud computing. Many researchers have developed various solutions for effective resource allocation of data centers. The fuzzy decision making scheme has been recognized as an effective candidate for this problem. The solution, however, has a limitation that linguistic parameters are used as input in the selection of suitable VM and PM, causing subjectivity and vagueness. In this paper, a new approach for resource allocation of virtual machines is proposed which employs the TOPSIS, analytic hierarchy process (AHP), grey theory, and the concept of entropy. The simulation results show that the proposed scheme achieves better load balancing and availability of the system with less VM migration compared to the existing schemes.

引用

页码：470 / 477

页数：8

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