Cluster-based localization in wireless sensor networks

Localization is an important challenge in wireless sensor networks (WSN). Localization usually refers to the process of dynamically determining the position(s) of one or more node(s) in a larger network. The challenge lies in efficiently providing "acceptable" accuracy while conforming to the many constraints of WSNs. We propose a Cluster-based Partial Localization (CPL) to provide efficient localization, where the focus is on providing scalable partial localization suitable to a large and high-density network. CPL utilizes both a computationally-intensive localization technique (non-metric MDS) and a less intensive triangulation to achieve balance between complexity and performance. Clustering is utilized to select a subset of nodes to perform the non-metric MDS localization and then extend to the rest of the network. We show, with simulation results, that CPL will provide a considerable reduction in both computation and communication, while still yielding an acceptable accuracy.