An Energy-efficient Migration Model of Processes with Virtual Machines in a Server Cluster

Author(s):  
Ryo Watanabe ◽  
Dilawaer Duolikun ◽  
Tomoya Enokido ◽  
Makoto Takizawa
2017 ◽  
Vol 8 (2) ◽  
pp. 20-36
Author(s):  
Yu Cai

Energy efficient virtual machines (VM) management and distribution on cloud platforms is an important research subject. Mapping VMs into PMs (Physical Machines) requires knowing the capacity of each PM and the resource requirements of the VMs. It should also take into accounts of VM operation overheads, the reliability of PMs, Quality of Service (QoS) in addition to energy efficiency. In this article, the authors propose an energy efficient statistical live VM placement scheme in a heterogeneous server cluster. Their scheme supports VM requests scheduling and live migration to minimize the number of active servers in order to save the overall energy in a virtualized server cluster. Specifically, the proposed VM placement scheme incorporates all VM operation overheads in the dynamic migration process. In addition, it considers other important factors in relation to energy consumption and is ready to be extended with more considerations on user demands. The authors conducted extensive evaluations based on HPC jobs in a simulated environment. The results prove the effectiveness of the proposed scheme.


2014 ◽  
Vol 573 ◽  
pp. 537-542
Author(s):  
Iniya E. Nehru ◽  
Saswati Mukherjee ◽  
Jocelyn T. Noel

Cloud computing is a platform that provides different services for the Internet users and companies on a pay-as-you-use basis. Services are provided through the datacenters which are available all over the world. One of the major problems faced by the service providers is the huge amount of energy consumed at the Datacenter. In todays world, where the environmental factors are the most talked about, energy efficient management of Datacenters has to be given due importance. In this paper a migration model is proposed for migration of job between virtual machines by considering the energy consumed and deadline as crucial factors.


2017 ◽  
Vol 26 (1) ◽  
pp. 113-128
Author(s):  
Gamal Eldin I. Selim ◽  
Mohamed A. El-Rashidy ◽  
Nawal A. El-Fishawy

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