Energy efficient wireless packet scheduling and fair queuing

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As embedded systems are being networked, often wirelessly, an increasingly larger share of their total energy budget is due to the communication. This necessitates the development of power management techniques that address communication subsystems, such as radios, as opposed to computation subsystems, such as embedded processors, to which most of the research effort thus far has been devoted. In this paper, we present techniques for energy efficient packet scheduling and fair queuing in wireless communication systems. Our techniques are based on an extensive slack management approach that dynamically adapts the output rate of the system in accordance with the input packet arrival rate. We use a recently proposed radio power management technique, dynamic modulation scaling (DMS), as a control knob to enable energy-latency trade-offs during wireless packet transmission. We first analyze a single input stream scenario, and describe a rate adaptation technique that results in significantly lower energy consumption (reductions of up to 10 ×), while still bounding the resulting packet delays. By appropriately setting the various parameters of our algorithm, the system can be made to traverse the energy-latency-fidelity trade-off space. We extend our techniques to a multiple input stream scenario, and present E 2 WFQ , an energy efficient version of the weighted fair queuing (WFQ) algorithm for fair packet scheduling. Simulation results show that large energy savings can be obtained through the use of E 2 WFQ , with only a small, bounded increase in worst case packet latency. Further, our results demonstrate that E 2 WFQ does not adversely affect the throughput allocation (and hence, fairness) of WFQ.