Model-driven energy-aware rate adaptation

Abstract

Rate adaptation in WiFi networks has received significant attention recently. However, most existing work focuses on selecting the rate to maximize throughput. How to select a data rate to minimize energy consumption is an important yet under-explored topic. This problem is becoming increasingly important with the rapidly increasing popularity of MIMO deployment, because MIMO offers diverse rate choices (e.g., the number of antennas, the number of streams, modulation, and FEC coding) and selecting the appropriate rate has significant impact on power consumption. In this paper, we first use extensive measurement to develop a simple yet accurate energy model for 802.11n wireless cards. Then we use the models to drive the design of energy-aware rate adaptation scheme. A major benefit of a model-based rate adaptation is that applying a model allows us to eliminate frequent probes in many existing rate adaptation schemes so that it can quickly converges to the appropriate data rate. We demonstrate the effectiveness of our approach using trace-driven simulation and real implementation in a wireless testbed.