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Exploiting heterogeneity in grid computing for energy-efficient resource allocation


Garg, SK and Buyya, R, Exploiting heterogeneity in grid computing for energy-efficient resource allocation, Proceedings of the 17th International Conference on Advanced Computing and Communications, 14-17 December 2009, Bangalore, India, pp. 53-59. (2009) [Refereed Conference Paper]

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Copyright 2009 Advanced Computing and Communications Society

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The growing computing demand from industry and academia has lead to excessive power consumption which not only impacting long term sustainability of Grids like infrastructure in terms of energy cost but also from environmental perspective. The problem can be addressed by replacing with more energy efficient infrastructures, but the process of switching to new infrastructure is not only costly but also time consuming. Grid being consist of several HPC centers under different administrative domain, make problem more difficult. Thus, for reduction in energy consumption, we address the challenge by effectively distributing compute-intensive parallel applications on grid. We presented a metascheduling algorithm which exploits the heterogeneous nature of Grid to achieve reduction in energy consumption. Simulation results show that out algorithm HAMA can significantly improve the energy efficiency of global grids by a factor of typically 23% and as much as a factor of 50% in some cases while meeting user's QoS requirements.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Environmental Policy, Climate Change and Natural Hazards
Objective Group:Mitigation of climate change
Objective Field:Management of greenhouse gas emissions from information and communication services
UTAS Author:Garg, SK (Dr Saurabh Garg)
ID Code:93906
Year Published:2009
Deposited By:Information and Communication Technology
Deposited On:2014-08-21
Last Modified:2014-12-08

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