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In this paper the authors examine the problem of energy-aware resource allocation for hosting long-term services or on-demand compute jobs in clusters, e.g., deployed as part of computing infrastructures. They formalize the problem as three constrained optimization problems: maximize job performance under power consumption constraints, minimize power consumption under job performance constraints, and optimize a linear combination of power consumption and job performance. These problems are NP-hard but, given an instance, a bound on the optimal solution can be computed via a rational linear program. They propose polynomial heuristics for all three problems. Simulation experiments show that in all three cases some heuristics can achieve results close to optimal, i.e., lead to good job performance while conserving energy.
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