Information-Based Energy Efficient Sensor Selection in Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are mainly characterized by deployment of biomedical sensors around human body which transmit vital signs measurements about healthy status to the coordinator. Depending on the relevance between symptoms and diseases, it may not be necessary for every sensors to transmit its measurements for diagnoses. This paper shows how the relevance can be exploited on the Medium Access Control (MAC) layer by utilizing the mutual information. A theoretical framework is developed for sensor scheduling under an operation cost constraint. It is shown that the compact subset of sensors can be found to provide necessary information for timely and correct diagnoses. Based on the theoretical framework, an algorithm combining sensor selection and information gain is then designed. Simulation results show that the algorithm achieves high performance in terms of energy, latency and collision rate.