Energy-aware service allocation

In this paper we study the problem of energy-aware resource allocation for hosting long-term services or on-demand computing jobs in clusters, e.g., deployed as part of computing infrastructures. We 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. We 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.

► Comparison of algorithms to a bound on the optimal solution.
► Guarantee of maximum energy consumption.
► Guarantee of minimum quality of service.