Scheduling algorithms for optimizing the tradeoffs between delay, queue size and energy

In this paper we propose energy-aware scheduling algorithms that aim to optimize the tradeoff between energy consumption and traditional performance measures such as queue size and delay. We use the power-rate function f(x)= c+x^α for x >; 0 and f(0)= 0 to model the energy consumption. Scheduling algorithms have been studied in the past for the special case in which the base power c= 0. In general the base power c can be significant. We propose a batch-based scheduling algorithm that can keep the energy consumption to asymptotically optimal while paying for a logarithmic factor in the queue size. Such a tradeoff is best possible. We also characterize the energy-delay tradeoff for a rate-adaptive version of the Weighted Fair Queuing scheduling algorithm.