Towards Green Cloud Computing an Algorithmic Approach for Energy Minimization in Cloud Data Centers
The article presents an efficient energy optimization framework based on dynamic resource scheduling for VM migration in cloud data centers. This increasing number of cloud data centers all over the world are consuming a vast amount of power and thus, exhaling a huge amount of CO2 that has a strong...
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Published in | International journal of cloud applications and computing Vol. 9; no. 1; pp. 59 - 81 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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IGI Global
01.01.2019
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Abstract | The article presents an efficient energy optimization framework based on dynamic resource scheduling for VM migration in cloud data centers. This increasing number of cloud data centers all over the world are consuming a vast amount of power and thus, exhaling a huge amount of CO2 that has a strong negative impact on the environment. Therefore, implementing Green cloud computing by efficient power reduction is a momentous research area. Live Virtual Machine (VM) migration, and server consolidation technology along with appropriate resource allocation of users' tasks, is particularly useful for reducing power consumption in cloud data centers. In this article, the authors propose algorithms which mainly consider live VM migration techniques for power reduction named “Power_reduction” and “VM_migration.” Moreover, the authors implement dynamic scheduling of servers based on sequential search, random search, and a maximum fairness search for convenient allocation and higher utilization of resources. The authors perform simulation work using CloudSim and the Cloudera simulator to evaluate the performance of the proposed algorithms. Results show that the proposed approaches achieve around 30% energy savings than the existing algorithms. |
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AbstractList | The article presents an efficient energy optimization framework based on dynamic resource scheduling for VM migration in cloud data centers. This increasing number of cloud data centers all over the world are consuming a vast amount of power and thus, exhaling a huge amount of CO2 that has a strong negative impact on the environment. Therefore, implementing Green cloud computing by efficient power reduction is a momentous research area. Live Virtual Machine (VM) migration, and server consolidation technology along with appropriate resource allocation of users' tasks, is particularly useful for reducing power consumption in cloud data centers. In this article, the authors propose algorithms which mainly consider live VM migration techniques for power reduction named “Power_reduction” and “VM_migration.” Moreover, the authors implement dynamic scheduling of servers based on sequential search, random search, and a maximum fairness search for convenient allocation and higher utilization of resources. The authors perform simulation work using CloudSim and the Cloudera simulator to evaluate the performance of the proposed algorithms. Results show that the proposed approaches achieve around 30% energy savings than the existing algorithms. |
Author | Atik, Syeda Tanjila Jeba, Jenia Afrin Roy, Shanto Whaiduzzaman, Md Rashid, Mahbub Or |
AuthorAffiliation | Jahangirnagar University, Dhaka, Bangladesh |
AuthorAffiliation_xml | – name: Jahangirnagar University, Dhaka, Bangladesh |
Author_xml | – sequence: 1 givenname: Jenia surname: Jeba middlename: Afrin fullname: Jeba, Jenia Afrin organization: Jahangirnagar University, Dhaka, Bangladesh – sequence: 2 givenname: Shanto surname: Roy fullname: Roy, Shanto organization: Jahangirnagar University, Dhaka, Bangladesh – sequence: 3 givenname: Mahbub surname: Rashid middlename: Or fullname: Rashid, Mahbub Or organization: Jahangirnagar University, Dhaka, Bangladesh – sequence: 4 givenname: Syeda surname: Atik middlename: Tanjila fullname: Atik, Syeda Tanjila organization: Jahangirnagar University, Dhaka, Bangladesh – sequence: 5 givenname: Md surname: Whaiduzzaman fullname: Whaiduzzaman, Md organization: Jahangirnagar University, Dhaka, Bangladesh |
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SubjectTerms | Algorithms Cloud computing Computer centers Data centers Power consumption Resource allocation Resource scheduling Resource utilization Searching Virtual environments |
Title | Towards Green Cloud Computing an Algorithmic Approach for Energy Minimization in Cloud Data Centers |
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