The optimization of resources allocation to minimize energy consumption within data center in cloud

Cloud computing is a ubiquitous technology in computer science which provides some advantages to current users of modern computing. The advantages of these services are extremely significant, but the data centers that offer this kind of service are suffering from over power...

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Main Authors: Ayob, Fahrul Hakim, Jayatis, Punaya, Subramaniam, Shamala
Format: Article
Language:English
Published: World Academy of Research in Science and Engineering 2019
Online Access:http://psasir.upm.edu.my/id/eprint/82548/
http://psasir.upm.edu.my/id/eprint/82548/1/The%20optimization%20of%20resources%20allocation%20to%20minimize%20energy%20consumption%20within%20data%20center%20in%20cloud.pdf
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author Ayob, Fahrul Hakim
Jayatis, Punaya
Subramaniam, Shamala
author_facet Ayob, Fahrul Hakim
Jayatis, Punaya
Subramaniam, Shamala
author_sort Ayob, Fahrul Hakim
building UPM Institutional Repository
collection Online Access
description Cloud computing is a ubiquitous technology in computer science which provides some advantages to current users of modern computing. The advantages of these services are extremely significant, but the data centers that offer this kind of service are suffering from over power consumption that impose serious threats to the environment due to the emission of carbon dioxide to the atmosphere.Because of some disadvantages in Dynamic Voltage Frequency Scheduling (DVFS), this paper proposes a cloud scheduling algorithm adapted from Dynamic Resource Allocation Method (DRA) to be developed with the goal of dynamically virtual machines (VMs) migration when resource utilization reaches above or below threshold readings in order to optimize the power consumption towards energy saving in cloud data center. The advantage of having VMs migration mechanism is to have the capability to consolidate VMs in order to optimize the capacity of resources utilization. Thus, at the same time it has the capability to switch off some under-loaded hosts which are below the threshold reading. So in this research, our proposed algorithm is going to optimize the total running machine by switching off the hosts with below 30% of CPU power consumption and migrate all the VMs run under it to other hosts.But, for over-utilized hosts with more than 90% of computing resources consumption, the migration of some VMs run under it will be carried out. When comparing with DVFS in a set of experiment, the proposed algorithm is better in terms of lower power consumption.
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spelling upm-825482021-06-10T23:45:17Z http://psasir.upm.edu.my/id/eprint/82548/ The optimization of resources allocation to minimize energy consumption within data center in cloud Ayob, Fahrul Hakim Jayatis, Punaya Subramaniam, Shamala Cloud computing is a ubiquitous technology in computer science which provides some advantages to current users of modern computing. The advantages of these services are extremely significant, but the data centers that offer this kind of service are suffering from over power consumption that impose serious threats to the environment due to the emission of carbon dioxide to the atmosphere.Because of some disadvantages in Dynamic Voltage Frequency Scheduling (DVFS), this paper proposes a cloud scheduling algorithm adapted from Dynamic Resource Allocation Method (DRA) to be developed with the goal of dynamically virtual machines (VMs) migration when resource utilization reaches above or below threshold readings in order to optimize the power consumption towards energy saving in cloud data center. The advantage of having VMs migration mechanism is to have the capability to consolidate VMs in order to optimize the capacity of resources utilization. Thus, at the same time it has the capability to switch off some under-loaded hosts which are below the threshold reading. So in this research, our proposed algorithm is going to optimize the total running machine by switching off the hosts with below 30% of CPU power consumption and migrate all the VMs run under it to other hosts.But, for over-utilized hosts with more than 90% of computing resources consumption, the migration of some VMs run under it will be carried out. When comparing with DVFS in a set of experiment, the proposed algorithm is better in terms of lower power consumption. World Academy of Research in Science and Engineering 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/82548/1/The%20optimization%20of%20resources%20allocation%20to%20minimize%20energy%20consumption%20within%20data%20center%20in%20cloud.pdf Ayob, Fahrul Hakim and Jayatis, Punaya and Subramaniam, Shamala (2019) The optimization of resources allocation to minimize energy consumption within data center in cloud. International Journal of Advanced Trends in Computer Science and Engineering, 8 (1 spec. 4). pp. 340-349. ISSN 2278-3091 http://www.warse.org/IJATCSE/years/archivesDetiles/?heading=Volume%208%20No.%201.4%20(2019)%20S%20I 10.30534/ijatcse/2019/5281.42019
spellingShingle Ayob, Fahrul Hakim
Jayatis, Punaya
Subramaniam, Shamala
The optimization of resources allocation to minimize energy consumption within data center in cloud
title The optimization of resources allocation to minimize energy consumption within data center in cloud
title_full The optimization of resources allocation to minimize energy consumption within data center in cloud
title_fullStr The optimization of resources allocation to minimize energy consumption within data center in cloud
title_full_unstemmed The optimization of resources allocation to minimize energy consumption within data center in cloud
title_short The optimization of resources allocation to minimize energy consumption within data center in cloud
title_sort optimization of resources allocation to minimize energy consumption within data center in cloud
url http://psasir.upm.edu.my/id/eprint/82548/
http://psasir.upm.edu.my/id/eprint/82548/
http://psasir.upm.edu.my/id/eprint/82548/
http://psasir.upm.edu.my/id/eprint/82548/1/The%20optimization%20of%20resources%20allocation%20to%20minimize%20energy%20consumption%20within%20data%20center%20in%20cloud.pdf