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A Comparison Study of Chi-square and Uniform Distributions of Mesh Clients by WMN-PSODGA Simulation System for RIWM and LDIWM Router Replacement Methods Read chapter Read first chapter

2022 | OriginalPaper | Chapter

An Energy-Efficient Algorithm to Make Virtual Machines Migrate in a Server Cluster

Authors : Dilawaer Duolikun, Tomoya Enokido, Leonard Barolli, Makoto Takizawa

Published in: Advances on Broad-Band Wireless Computing, Communication and Applications

Publisher: Springer International Publishing

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Abstract

It is critical to reduce the energy consumption of clusters of servers. Through virtual machines, applications can take advantage of virtual services independent of heterogeneity and locations of servers. Here, we have to select a host server and a virtual machine on the server to perform an application process so that the total energy consumption of servers can be reduced. We first improve the MI (Monotonically Increasing) algorithm previously proposed to simply estimate the energy consumption of servers only by using the number of active processes. Then, we propose an MIM (MI Migration) algorithm to reduce the energy consumption of servers by using the improved MI algorithm. Here, a virtual machine on a host server migrates to a guest server to reduce the total energy consumption of the servers. In the evaluation, we show the execution time and energy consumption of servers in a cluster can be reduced in the MIM algorithm compared with other algorithms.

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previous chapter Performance Evaluation of WMNs by WMN-PSOHC Hybrid Simulation System Considering Different Number of Mesh Routers and Chi-Square Distribution of Mesh Clients
next chapter Evaluation of Focused Beam Routing Protocol for Different Applications of Underwater Sensor Networks
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Metadata
Title
An Energy-Efficient Algorithm to Make Virtual Machines Migrate in a Server Cluster
Authors
Dilawaer Duolikun
Tomoya Enokido
Leonard Barolli
Makoto Takizawa
Copyright Year
2022
Book
Advances on Broad-Band Wireless Computing, Communication and Applications

Print ISBN: 978-3-030-90071-7

Electronic ISBN: 978-3-030-90072-4

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-030-90072-4_3