Cluster-based service discovery for heterogeneous wireless sensor networks

We propose an energy-efficient service discovery protocol for heterogeneous wireless sensor networks. Our solution exploits a cluster overlay, where the clusterhead nodes form a distributed service registry. A service lookup results in visiting only the clusterhead nodes. We aim for minimizing the communication costs during discovery of services and maintenance of a functional distributed service registry. To achieve these objectives we propose a clustering algorithm which makes decisions based on 1-hop neighbourhood information, avoids chain reactions and constructs a set of sparsely distributed clusterheads. We analyse how the properties of the clustering structure influence the performance of the service discovery protocol, by comparing our proposed clustering algorithm with DMAC. We evaluate the performance and the tradeoffs between the cluster-based service discovery approaches and the traditional flood-based solutions. We investigate the level of network heterogeneity where clustering is feasible for implementation in a wireless sensor network. Our analysis shows that cluster-based solutions are best suited for heterogeneous dense networks, with limited dynamics.