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| 001 |
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| 005 |
20151201120132.0 |
| 006 |
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| 007 |
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| 008 |
100427s2010 txu sbm 000 0 eng d |
| 035 |
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|a (OCoLC)ocn609670215
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| 035 |
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|a (OCoLC)609670215
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| 035 |
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|a (TxCM)http://hdl.handle.net/1969.1/ETD-TAMU-3182
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| 040 |
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|a TXA
|c TXA
|d UtOrBLW
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| 049 |
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|a TXAM
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| 099 |
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|a 2008
|a Dissertation
|a 1969.1/ETD-TAMU-3182
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| 100 |
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|a Rincon Mateus, Cesar Augusto.
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| 245 |
1 |
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|a Dynamic resource allocation for energy management in data centers /
|c by Cesar Augusto Rincon Mateus.
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| 264 |
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1 |
|a [College Station, Tex.] :
|b [Texas A&M University],
|c [2010]
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| 300 |
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|a 1 online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 500 |
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|a "Major Subject: Industrial Engineering"
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| 500 |
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|a Title from author supplied metadata (automated record created 2010-03-12 12:08:51).
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| 502 |
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|b Doctor of Philosophy
|c Texas A&M University
|d 2008
|o http://hdl.handle.net/1969.1/ETD-TAMU-3182
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| 504 |
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|a Includes bibliographical references.
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| 516 |
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|a Text (Dissertation)
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|a In this dissertation we study the problem of allocating computational resources and managing applications in a data center to serve incoming requests in such a way that the energy usage, reliability and quality of service considerations are balanced. The problem is motivated by the growing energy consumption by data centers in the world and their overall inefficiency. This work is focused on designing flexible and robust strategies to manage the resources in such a way that the system is able to meet the service agreements even when the load conditions change. As a first step, we study the control of a Markovian queueing system with controllable number of servers and service rates (M=Mt=kt ) to minimize effort and holding costs. We present structural properties of the optimal policy and suggest an algorithm to find good performance policies even for large cases. Then we present a reactive/proactive approach, and a tailor-made wavelet-based forecasting procedure to determine the resource allocation in a single application setting; the method is tested by simulation with real web traces. The main feature of this method is its robustness and flexibility to meet QoS goals even when the traffic behavior changes. The system was tested by simulating a system with a time service factor QoS agreement. Finally, we consider the multi-application setting and develop a novel load consolidation strategy (of combining applications that are traditionally hosted on different servers) to reduce the server-load variability and the number of booting cycles in order to obtain a better capacity allocation.
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| 500 |
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|a Electronic resource.
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| 650 |
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|a Major Industrial Engineering.
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| 653 |
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|a Wavelets
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| 653 |
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|a Energy Management
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| 653 |
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|a Forecasting
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| 653 |
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|a Consolidation
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| 653 |
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|a Queueing Control
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| 653 |
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|a Reliability
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| 653 |
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|a Resource Allocation
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| 700 |
1 |
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|a Gautam, Natarajan,
|e thesis advisor.
|
| 856 |
4 |
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|u http://hdl.handle.net/1969.1/ETD-TAMU-3182
|z Link to OAK Trust copy
|t 0
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| 994 |
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|a C0
|b TXA
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| 948 |
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|a cataloged
|b h
|c 2010/4/27
|d c
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|
| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|d Available Online
|t 0
|e 2008 Dissertation 1969.1/ETD-TAMU-3182
|h Other scheme
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| 998 |
f |
f |
|a 2008 Dissertation 1969.1/ETD-TAMU-3182
|t 0
|l Available Online
|