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Cooperative Power-Aware Scheduling in Grid Computing Environments

Subrata, Riky; Zomaya, Albert Y. and Landfeldt, Björn LU (2010) In Journal of Parallel and Distributed Computing 70(2). p.84-91
Abstract
Energy usage and its associated costs have taken on a new level of significance in recent years. Globally, energy costs that include the cooling of server rooms are now comparable to hardware costs, and these costs are on the increase with the rising cost of energy. As a result, there are efforts worldwide to design more efficient scheduling algorithms. Such scheduling algorithm for grids is further complicated by the fact that the different sites in a grid system are likely to have different ownerships. As such, it is not enough to simply minimize the total energy usage in the grid; instead one needs to simultaneously minimize energy usage between all the different providers in the grid. Apart from the multitude of ownerships of the... (More)
Energy usage and its associated costs have taken on a new level of significance in recent years. Globally, energy costs that include the cooling of server rooms are now comparable to hardware costs, and these costs are on the increase with the rising cost of energy. As a result, there are efforts worldwide to design more efficient scheduling algorithms. Such scheduling algorithm for grids is further complicated by the fact that the different sites in a grid system are likely to have different ownerships. As such, it is not enough to simply minimize the total energy usage in the grid; instead one needs to simultaneously minimize energy usage between all the different providers in the grid. Apart from the multitude of ownerships of the different sites, a grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes as well as the communication links that connect the different nodes together. In this paper, we propose a cooperative, power-aware game theoretic solution to the job scheduling problem in grids. We discuss our cooperative game model and present the structure of the Nash Bargaining Solution. Our proposed scheduling scheme maintains a specified Quality of Service (QoS) level and minimizes energy usage between all the providers simultaneously; energy usage is kept at a level that is sufficient to maintain the desired QoS level. Further, the proposed algorithm is fair to all users, and has robust performance against inaccuracies in performance prediction information. (Less)
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author
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Parallel and Distributed Computing
volume
70
issue
2
pages
84 - 91
publisher
Elsevier
external identifiers
  • scopus:72749127771
ISSN
0743-7315
DOI
10.1016/j.jpdc.2009.09.003
language
English
LU publication?
no
id
81e828bf-eddd-4685-8b90-6d2b08fcb532 (old id 3131078)
date added to LUP
2012-10-19 11:38:23
date last changed
2018-06-17 04:20:02
@article{81e828bf-eddd-4685-8b90-6d2b08fcb532,
  abstract     = {Energy usage and its associated costs have taken on a new level of significance in recent years. Globally, energy costs that include the cooling of server rooms are now comparable to hardware costs, and these costs are on the increase with the rising cost of energy. As a result, there are efforts worldwide to design more efficient scheduling algorithms. Such scheduling algorithm for grids is further complicated by the fact that the different sites in a grid system are likely to have different ownerships. As such, it is not enough to simply minimize the total energy usage in the grid; instead one needs to simultaneously minimize energy usage between all the different providers in the grid. Apart from the multitude of ownerships of the different sites, a grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes as well as the communication links that connect the different nodes together. In this paper, we propose a cooperative, power-aware game theoretic solution to the job scheduling problem in grids. We discuss our cooperative game model and present the structure of the Nash Bargaining Solution. Our proposed scheduling scheme maintains a specified Quality of Service (QoS) level and minimizes energy usage between all the providers simultaneously; energy usage is kept at a level that is sufficient to maintain the desired QoS level. Further, the proposed algorithm is fair to all users, and has robust performance against inaccuracies in performance prediction information.},
  author       = {Subrata, Riky and Zomaya, Albert Y. and Landfeldt, Björn},
  issn         = {0743-7315},
  language     = {eng},
  number       = {2},
  pages        = {84--91},
  publisher    = {Elsevier},
  series       = {Journal of Parallel and Distributed Computing},
  title        = {Cooperative Power-Aware Scheduling in Grid Computing Environments},
  url          = {http://dx.doi.org/10.1016/j.jpdc.2009.09.003},
  volume       = {70},
  year         = {2010},
}