A bio-inspired distributed clustering algorithm for wireless sensor networks

Wireless sensor networks (WSNs) have emerged in strategic applications such as target detection, localization, and tracking in battlefields, where the large-scale nature renders centralized control prohibitive. In addition, the finite batteries in sensor nodes demand energy-aware network control. In this paper, we propose an energy-efficient topology management model that allows clustered nodes to act upon imminent targets in a purely distributed and autonomous fashion, which is inspired by the biological inter-cell lateral induction models. In particular, nodes in the target vicinity collaborate to form clusters based on their relative observation quality values. The energy efficiency of the proposed approach is examined against reference protocols.