An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers
Autor: | Nicola Blefari-Melazzi, Fabio D'Andreagiovanni, Claudia Canali, Luca Chiaraviglio, Mohammad Shojafar, Riccardo Lancellotti |
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Přispěvatelé: | Department of Electronics [Torino] (DELEN), Politecnico di Torino = Polytechnic of Turin (Polito), Centre National de la Recherche Scientifique (CNRS), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS) |
Rok vydání: | 2018 |
Předmět: |
Control and Optimization
Computer science Distributed computing Cloud computing 02 engineering and technology Maintenance engineering [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] Server 0202 electrical engineering electronic engineering information engineering ComputingMilieux_MISCELLANEOUS Settore ING-INF/03 - Telecomunicazioni Renewable Energy Sustainability and the Environment business.industry 020206 networking & telecommunications [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO] Energy consumption Load balancing (computing) Computational Theory and Mathematics Hardware and Architecture 020201 artificial intelligence & image processing Data center [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] Central processing unit Electricity business Software |
Zdroj: | IEEE Transactions on Sustainable Computing IEEE Transactions on Sustainable Computing, IEEE, 2018, 3 (4), pp.274-288 |
ISSN: | 2377-3790 2377-3782 |
Popis: | We target the problem of managing the power states of the servers in a Cloud Data Center (CDC) to jointly minimize the electricity consumption and the maintenance costs derived from the variation of power (and consequently of temperature) on the servers’ CPU. More in detail, we consider a set of virtual machines (VMs) and their requirements in terms of CPU and memory across a set of Time Slot (TSs). We then model the consumed electricity by taking into account the VMs processing costs on the servers, the costs for transferring data between the VMs, and the costs for migrating the VMs across the servers. In addition, we employ a material-based fatigue model to compute the maintenance costs needed to repair the CPU, as a consequence of the variation over time of the server power states. After detailing the problem formulation, we design an original algorithm, called Maintenance and Electricity Costs Data Center (MECDC), to solve it. Our results, obtained over several scenarios from a real CDC, show that MECDC largely outperforms two reference algorithms, which instead either target the load balancing or the energy consumption of the servers. |
Databáze: | OpenAIRE |
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