Dynamic power management for QoS-aware applications
Reducing the power requirement of large IT infrastructures is becoming a major concern. Energy savings can be achieved with hardware and/or software solutions; in particular, modern CPUs can operate at different power levels that can be selected by software: low power modes reduce energy consumption...
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| Published in | Sustainable computing informatics and systems Vol. 3; no. 4; pp. 231 - 248 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Inc
01.12.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2210-5379 |
| DOI | 10.1016/j.suscom.2013.02.001 |
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| Abstract | Reducing the power requirement of large IT infrastructures is becoming a major concern. Energy savings can be achieved with hardware and/or software solutions; in particular, modern CPUs can operate at different power levels that can be selected by software: low power modes reduce energy consumption at the cost of lowering also the CPU processing rate. In this paper we address the problem of reducing energy consumption of a large-scale distributed application subject to Service Level Agreements requiring a maximum allowed response time. Specifically, we propose Energy Aware reconfiguration of software SYstems (EASY), an on-line algorithm for dynamically adjusting the processing speed of individual devices such that the average system response time is kept below a predefined threshold, and the total power consumption is minimized. EASY uses a queueing networks performance model to proactively drive the reconfiguration process, so that the number of individual reconfiguration actions is reduced. We formulate the energy conservation problem as a Mixed Integer Programming problem, for which we propose a heuristic solution technique. Numerical experiments show that the heuristic produces almost optimal results at a substantially lower computational cost. Therefore, EASY can be effectively applied on-line to make a large system energy-proportional. |
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| AbstractList | Reducing the power requirement of large IT infrastructures is becoming a major concern. Energy savings can be achieved with hardware and/or software solutions; in particular, modern CPUs can operate at different power levels that can be selected by software: low power modes reduce energy consumption at the cost of lowering also the CPU processing rate. In this paper we address the problem of reducing energy consumption of a large-scale distributed application subject to Service Level Agreements requiring a maximum allowed response time. Specifically, we propose Energy Aware reconfiguration of software SYstems (EASY), an on-line algorithm for dynamically adjusting the processing speed of individual devices such that the average system response time is kept below a predefined threshold, and the total power consumption is minimized. EASY uses a queueing networks performance model to proactively drive the reconfiguration process, so that the number of individual reconfiguration actions is reduced. We formulate the energy conservation problem as a Mixed Integer Programming problem, for which we propose a heuristic solution technique. Numerical experiments show that the heuristic produces almost optimal results at a substantially lower computational cost. Therefore, EASY can be effectively applied on-line to make a large system energy-proportional. |
| Author | Mirandola, Raffaela Marzolla, Moreno |
| Author_xml | – sequence: 1 givenname: Moreno surname: Marzolla fullname: Marzolla, Moreno email: marzolla@cs.unibo.it organization: Università di Bologna, Dipartimento di Scienze dell’Informazione, Mura A. Zamboni 7, I-40126 Bologna, Italy – sequence: 2 givenname: Raffaela surname: Mirandola fullname: Mirandola, Raffaela email: mirandola@elet.polimi.it organization: Politecnico di Milano, Dipartimento di Elettronica e Informazione, Piazza Leonardo da Vinci, I-20133 Milano, Italy |
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| Keywords | Performance modeling Power management Energy proportional computing SLA management |
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| Title | Dynamic power management for QoS-aware applications |
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