Paper Info
Title
Game theory based dynamic resource allocation for hybrid environment with cloud and big data application
Abstract
Virtualization based cloud and big data applications have been widely adopted in various fields. Because deploying the big data applications on the cloud will cause obvious performance degradation, the cloud and big data applications are provided with fixed resource separately. However, the traditional fixed resource allocation mechanism has two drawbacks: (1) low resource utility and (2) unresponsiveness to the performance degradation. To address these drawbacks, the cloud and big data hybrid environment is designed, where fair resource allocation is used to ensure fairness between cloud and big data applications while virtual machine migration is used to make each virtual machine in cloud application reach its own satisfactory. Herein, game theory is used to model the conflict and negotiation between cloud and big data applications. Firstly, the Nash Equilibrium is used to discover the best strategy for both applications. Secondly, as for virtual machine migration, we use Nash Bargaining game to present the situation where virtual machines compete for more resources allocation while their minimal demand is ensured. Finally, experiments are carried out to prove that the hybrid environment outperforms the traditional method both in resource utility and application performance.
Year
DOI
Venue
2014
10.1109/SMC.2014.6974065
SMC
Keywords
DocType
ISSN
fixed resource allocation mechanism,big data,cloud application,virtual machines,Nash equilibrium,resource allocation,unresponsiveness,performance degradation,game theory,cloud,game theory based dynamic resource allocation,low resource utility,virtualisation,big data hybrid environment,virtual machine migration,performance evaluation,Big Data,data virtualization,cloud computing,big data application,Nash bargaining game
Conference
1062-922X
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Junxue Zhang1193.37
Fang Dong220235.44
Dian Shen3105.22
Junzhou Luo41257153.97