Heuristics based server consolidation with residual resource defragmentation in cloud data centers |
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| Affiliation: | 1. Faculty of Mechanical Engineering, University of Kashan, Kashan, Islamic Republic of Iran.;2. Institute of Nanoscience & Nanotechnology, University of Kashan, Kashan, Islamic Republic of Iran;1. Department of Computer Science and Technology, Tsinghua University, Beijing, China;2. Intel Corporation, Beijing, China;1. Institute of Analysis, Johannes Kepler University Linz, Altenberger Strasse 69, 4040 Linz, Austria;2. DAMTP, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, UK;1. Department of Electrical Engineering, IIT Bombay, Powai, Mumbai 400076, India;2. Department of Electronics and Information Technology, Ministry of Communications and IT, Govt of India, Delhi, 110003, India;3. Department of Electrical Engineering, IIT Hyderabad, Ordinance Factory Estate, Yeddumailaram, Andhra Pradesh 502205, India |
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| Abstract: | Server Consolidation is one of the foremost concerns associated with the effective management of a Cloud Data Center as it has the potential to accomplish significant reduction in the overall cost and energy consumption. Most of the existing works on Server Consolidation have focused only on reducing the number of active physical servers (PMs) using Virtual Machine (VM) Live Migration. But, along with reducing the number of active PMs, if a consolidation approach reduces residual resource fragmentation, the residual resources can be efficiently used for new VM allocations, or VM reallocations, and some future migrations can also be reduced. None of the existing works have explicitly focused on reducing residual resource fragmentation along with reducing the number of active PMs to the best of our knowledge. We propose RFAware Server Consolidation, a heuristics based server consolidation approach which performs residual resource defragmentation along with reducing the number of active PMs in cloud data centers. |
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| Keywords: | Server consolidation Cloud data center IaaS Virtualization Bin packing Resource fragmentation |
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