Abstract
Due to the rapid growth in the data storage and data processing demands, the energy consumption of data centers is becoming a key challenge. Live migration of Virtual Machine (VM) is commonly proposed to reduce energy consumption and to optimize resource usage in the literature although itcomes withessential drawbacks such as migration cost and Service Level Agreement Violation (SLAV). Anovel efficient resource management policy for virtualized data centers which optimizes the number of resources to meet requirements of dynamic workloads without migration is proposed in this paper. The proposed approach contains an experiment based prediction module. Energy-performance trade off relies on comparison of the predicted and the active number of servers periodically. The performance evaluations of the proposed approach are performed by using real-world workload traces from Planet Lab. The proposed algorithm is also compared to the other techniques proposed in the literature based on VM migration.
Original language | English |
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Title of host publication | Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 |
Editors | Meikang Qiu |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 240-244 |
Number of pages | 5 |
ISBN (Electronic) | 9781509024025 |
DOIs | |
Publication status | Published - 30 Jun 2016 |
Event | 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 - New York, United States Duration: 9 Apr 2016 → 10 Apr 2016 |
Publication series
Name | Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 |
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Conference
Conference | 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 |
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Country/Territory | United States |
City | New York |
Period | 9/04/16 → 10/04/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Keywords
- Cloud Computing
- Energy Efficiency
- Green Computing
- Resource Management
- VM Migration