DocumentCode :
256508
Title :
Energy efficient resource management for Cloud Computing Environment
Author :
Selmy, H.A. ; Alkabani, Y. ; Mohamed, H.K.
Author_Institution :
Dept. of Comput. & Syst. Eng., Ain Shams Univ., Cairo, Egypt
fYear :
2014
fDate :
22-23 Dec. 2014
Firstpage :
415
Lastpage :
420
Abstract :
Cloud computing is a highly scalable and cost - effective infrastructure for running High Performance Computing, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. Hence, energy efficient solutions are required to minimize this energy consumption. The energy efficient solutions aim at lowering the energy usage of data centers because computing applications and data are growing so quickly that increasingly larger servers and disks are needed to process them fast enough within the required time period so here we reduce the energy consumption by an average of 40% over previously introduced methods. So in datacenters, the number of physical machines can be reduced using virtualization by consolidating virtual machines onto shared servers and enabling them to migrate according to migration policy. This paper presents virtual machines migration and selection policies to boost Cloud Computing Environment energy efficiency and performance.
Keywords :
cloud computing; computer centres; energy consumption; resource allocation; virtual machines; virtualisation; cloud computing environment; data center; energy consumption; energy efficient resource management; virtual machine migration; virtualization; Artificial neural networks; Clustering algorithms; Heuristic algorithms; History; Quality of service; Random access memory; Allocation; Cloud Computing; Cluster; Migration; Neural Network; Self Organized Map (SOM); Virtual machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering & Systems (ICCES), 2014 9th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4799-6593-9
Type :
conf
DOI :
10.1109/ICCES.2014.7030997
Filename :
7030997
Link To Document :
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