Boosting Data Center Performance Through Non-Uniform Power Allocation
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
Exploiting Platform Heterogeneity for Power Efficient Data Centers
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
Resource Management in the Autonomic Service-Oriented Architecture
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
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Efficient energy consumption in large sets of electric devices is a complex problem since it requires a balance between many competing factors. Presently, self-optimization techniques work expeditiously on small and relatively less complex problems. However, these techniques are not shown to be scalable on large and complex problems. In this paper we have used linear programming to optimize the use of energy in a typical environment that consists of large number of devices. Our initial results show that LP is fast, predictable and scalable. Moreover, we have also observed that modeling in LP is quite simple as compared to other self-optimization techniques.