A distributed cluster-based localization method for wireless sensor networks (original) (raw)

Node localization is a fundamental capability for several applications of Wireless Sensor Networks (WSN), such as security surveillance, fire detection, animal behavior monitoring, among others. Over the last decade, node localization in wireless sensor networks has evolved from centralized to distributed solutions. Therefore, more demanding conditions have arisen for new applications. These conditions come from massive node deployment and irregular topologies, requiring further analysis. In this paper, we present a method to reduce the signaling overhead due to a distributed localization procedure. This method consists of four stages: Based on the Awerbuch's γ synchronizer, the proposal divides the network into clusters. The cluster size is restricted by a growing factor defined by a cluster-head, i.e., a leader. Based on connectivity information, the distance between each pair of nodes, belonging to the same cluster, is calculated by the corresponding leader. Next, each leader solves locally a particular instance of the MultiDimensional Scaling (MDS) problem. Finally, a minimum set of beacons is selected on each cluster. This is in order to assemble each region into a global localization solution within a single system of reference. In our method, we turn the initial settlement into several smaller instances of the original problem which can be solved simultaneously and based on local resources. Simulation results show that this approach produces important savings on the required message exchange.