Profiling : an application assignment approach for green data centers
Data(s) |
2014
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Resumo |
In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution. |
Formato |
application/pdf |
Identificador | |
Publicador |
IEEE |
Relação |
http://eprints.qut.edu.au/78666/1/IECON_Final_Manuscript_Sept2014.pdf Vasudevan, Meera, Tian, Yu-Chu, Tang, Maolin, & Kozan, Erhan (2014) Profiling : an application assignment approach for green data centers. In 40th Annual Conference of the IEEE Industrial Electronics Society (IECON 2014), 29 October - 1 November 2014, Sheraton Hotel, Dallas, TX. (In Press) |
Direitos |
Copyright 2014 [please consult the author] |
Fonte |
School of Electrical Engineering & Computer Science; School of Mathematical Sciences; Science & Engineering Faculty |
Palavras-Chave | #080599 Distributed Computing not elsewhere classified #energy efficiency #linear programming #heuristic #optimization |
Tipo |
Conference Paper |