Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3495
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPatra, Manoj Kumar-
dc.contributor.authorPatel, Dimple-
dc.contributor.authorSahoo, Bibhudatta-
dc.contributor.authorTuruk, Ashok Kumar-
dc.date.accessioned2020-02-12T11:02:49Z-
dc.date.available2020-02-12T11:02:49Z-
dc.date.issued2020-01-
dc.identifier.citation10th International Conference on Cloud Computing, Data Science and Engineering (Confluence-2020), Noida, India, 29-31 January 2020.en_US
dc.identifier.urihttp://hdl.handle.net/2080/3495-
dc.descriptionCopyright of this document is with proceedings publisheren_US
dc.description.abstractCloud computing provides information technology based solutions to the end-users as a utility. Virtual machine or the virtualization technology is the backbone of implementing cloud computing technologies. However, such implementation encounters the problem of tremendous energy consumption. One of the foremost issues in implementing cloud computing is high energy consumption. This can be reduced to some extent by proper allocation and efficient utilization of resources. At present, containerization is one of the broadly discussed techniques as an alternative to traditional virtualization solutions. In this paper, we propose a game-theoretic approach for resource allocation and a containerized cloud architecture which drastically reduces energy consumption than a virtual machine based cloud. We have used Google cluster traces data set for our experiment in the cloud with virtual machine and containerized cloud. Experimental results show that the energy consumption is minimized in the containerized cloud than a cloud with virtual machines.en_US
dc.publisherIEEEen_US
dc.subjectCloud Computing Containeren_US
dc.subjectVirtual Machineen_US
dc.subjectGame Theoryen_US
dc.subjectVirtualization Techniqueen_US
dc.subjectResource Allocationen_US
dc.titleGame Theoretic Task Allocation to Reduce Energy Consumption in Containerized Clouden_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
2020-ICCCDSE-MKPatra-Game.pdfConference paper219.97 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.