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http://hdl.handle.net/11375/13348
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DC Field | Value | Language |
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dc.contributor.advisor | Down, Douglas G. | en_US |
dc.contributor.advisor | Karakostas, George | en_US |
dc.contributor.author | Maccio, Vincent J. | en_US |
dc.date.accessioned | 2014-06-18T17:03:41Z | - |
dc.date.available | 2014-06-18T17:03:41Z | - |
dc.date.created | 2013-09-17 | en_US |
dc.date.issued | 2013-10 | en_US |
dc.identifier.other | opendissertations/8169 | en_US |
dc.identifier.other | 9284 | en_US |
dc.identifier.other | 4595486 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/13348 | - |
dc.description.abstract | <p>As energy costs and energy used by server farms increase, so does the desire to implement energy-aware policies. Although under some cost functions, optimal policies for single as well as multiple server systems are known, large gaps in theoretical knowledge are present in the field. Specifically, there exists many widely used and non-trivial cost functions, where the corresponding optimal policy remains unknown. This work presents and leverages a model which allows for the exact analysis of these optimal policies with considerable generality, for on/off single server systems under a broad range of cost functions that are based on expected response time, energy usage and switching costs. Furthermore, from the results derived in the analysis, several applications and implications are presented and discussed. This includes the determination of routing probabilities to show a range of non-trivial optimal routing probabilities and server configurations when energy concerns are a factor.</p> | en_US |
dc.subject | stochastic modelling | en_US |
dc.subject | Markov chain | en_US |
dc.subject | energy-aware server | en_US |
dc.subject | Operational Research | en_US |
dc.subject | Power and Energy | en_US |
dc.subject | Software Engineering | en_US |
dc.subject | Statistical Models | en_US |
dc.subject | Operational Research | en_US |
dc.title | On Optimal Policies for Energy-Aware Servers | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Computing and Software | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 1.71 MB | Adobe PDF | View/Open |
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