Target Coverage-Aware Clustering in Directional Sensor Networks: A Distributed Approach

Abstract

Existing clustering algorithms for directional sensor networks mainly focused on maximizing network lifetime and/or data delivery performances. A distributed clustering algorithm named TRACE considering target coverage is proposed in this paper that improves the clustering performances, as well as, the sensing coverage in the network. TRACE is designed to operate in a fully distributed manner. It is also a light-weight clustering algorithm based on coverage and connectivity, where only single-hop neighborhood information is exploited by the nodes to determine cluster heads (CHs) and two-hop neighborhood messages for gateways. Moreover, a target-coverage algorithm is proposed, where the TRACE CHs try to activate the minimum number of sensor nodes in the network, as well as, greedily maximize the number of covered targets. To measure the performances, the TRACE system is implemented in Network Simulator version 3 (NS-3) and the simulation outcomes depict that the proposed TRACE performs better than the state-of-the-art work in terms of cluster-coverage ratio, network lifetime, and overhead.