On the Efficiency of Cluster-Based Approaches for Motion Detection Using Body Sensor Networks
Body Sensor Networks (BSN) are an emerging application that places sensors on the human body. Given that a BSN is typically powered by a battery, one of the most critical challenges is how to prolong the lifetime of all sensor nodes. Recently, using clusters to reduce the energy consumption of BSN has shown promising results. One of the important parameters in these cluster-based algorithms is the selection of Cluster Heads (CHs). Most prior works selected CHs either probabilistically or based on nodes' residual energy. In this paper, the authors first discuss the efficiency of cluster-based approaches for saving energy. They then propose a novel cluster head selection algorithm to maximize the lifetime of a BSN for motion detection.