Low-energy automated scheduling of computing resources

Abstract

The cost of electricity for datacenters is a substantial operational cost that can and should be managed, not only for saving energy, but also due to the ecologic commitment inherent to power consumption. This work proposes, formalizes and numerically evaluates LEAS, a low-energy scheduling model, for clearing scheduling markets, based on the maximization of welfare, subject to utility-level dependant energy costs. We promote energyefficient policies in management of datacenters, to enhance the efficiency of modernized datacenters. We focus specifically on linear power models, and the implications of the inherent fixed costs related to energy consumption of modern datacenters. We rigorously test the model by running multiple simulation scenarios derived from real workload traces, and evaluate the results using common statistical methods. We conclude with positive results and implications for long-term sustainable management of modern datacenters.

Sourcing Strategies for Energy-Efficient Virtual Organisations in Cloud Computing

“…The authors evaluate the balance between computing, storage and network resources on a formal basis. [11] proposes a low-energy scheduling model for the optimisation of energyefficiency and use a welfare-maximisation approach. However, these approaches are limited to the optimisation of energy efficiency of a single enterprise and do not consider joint GVOs.…”