Abstract
With the increased popularity of cloud computing, the number and scales of cloud data centers have kept growing at unprecedented speeds. In the meanwhile, the energy consumption by the data centers has kept commensurately increasing as well. Therefore, the focus of cloud resource management and scheduling has relatively shifted from mere performance to also energy efficiency. In this paper, we present a novel, Energy-Aware Task Scheduling framework that makes integrated exploitation of the two well-known energy saving techniques, DVFS and VM Reuse, on cloud task scheduling in a data center. We present our scheduling approach and framework via a specific algorithm, called EATS-FFD, that assumes FFD as its base scheduling policy. With minor modification, the presented framework can be made to work with a different base scheduling policy, resulting in a correspondingly different scheduling algorithm. Our approach achieves better energy-efficiency without sacrificing system QoS. The effectiveness of our approach is evaluated under various experimental scenarios using the Cloud Report tool running on the open source CloudSim platform.
Original language | English |
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Title of host publication | Proceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015 |
Editors | Calton Pu, Ajay Mohindra |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 493-500 |
Number of pages | 8 |
ISBN (Electronic) | 9781467372879 |
DOIs | |
State | Published - 19 Aug 2015 |
Event | 8th IEEE International Conference on Cloud Computing, CLOUD 2015 - New York, United States Duration: 27 Jun 2015 → 2 Jul 2015 |
Other
Other | 8th IEEE International Conference on Cloud Computing, CLOUD 2015 |
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Country/Territory | United States |
City | New York |
Period | 27/06/15 → 2/07/15 |
Keywords
- Cloud Computing
- DVFS
- Energy consumption
- Task Scheduling
- VM Reuse