Quality of Information and Energy Efficiency Optimization for Sensor Networks via Adaptive Sensing and Transmitting

Co-optimizing information quality and energy efficiency are an important but challenging problem in sensor networks, because of the interdependency that exists between them. For example, increasing sensor sampling rate will improve information quality but cost energy consumption, due to more traffic needed to be transmitted. To address this co-optimization issue, this paper first presents a novel quality/energy efficient metric, which models the relationship of sensing, processing, and transmitting with quality and energy. Then, based on the metrics, a quality-energy adapting system is developed to exploit base station scheduling priority and techniques such as batch processing and adaptive sampling to optimize both energy efficiency and overall quality. Our results have demonstrated the usefulness of this model and its feasibility for base station to runtime co-optimize both quality and energy under changing environment and network conditions.