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  1. M. E. Gebrehiwot, S. Aalto and P. Lassila, Near-optimal policies for energy-aware task assignment in server farms, in Proceedings of 2nd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation, 2017, Madrid, Spain (bib)
    Abstract: Rising energy costs and the push for green computing have inspired a lot of research effort towards energy efficient computing. Incorporating low energy sleep states in server farms is one of the proposed solutions. This paper studies the trade-off between energy and performance that is inherent in such solutions using the popular cost metric Energy- Response-time-Weighted-Sum (ERWS). We apply the Markov Decision Process (MDP) theory to the task assignment problem, and derive a near-optimal dynamic task assignment policy for minimizing the ERWS cost metric. Furthermore, we consider a performance constrained energy minimization problem, and provide an algorithm that builds a dynamic task assignment policy by choosing the right energy weight value for the ERWS cost metric. We also show that the resulting task assignment policy behaves like a modified version of the Join the Shortest Queue (JSQ), having a near-optimal performance by minimizing energy consumption while still obeying response time constraint.