Cluster-Based Localisation Method for Dense WSN: A Distributed Balance between Accuracy and Complexity Fixed by Cluster Size

Abstract

Localisation is a fundamental requirement for a monitoring and tracking system based on wireless sensor networks (WSN). In order to build an accurate set of measurements, sensor nodes must have information regarding their own position within a system of coordinates. When a considerable number of nodes are randomly scattered over a monitoring area, sensor nodes must be part of a self-organised system which provides a set of local position estimates. Nodes participate under very stringent conditions, for example, limited power supply and reduced computational capabilities. This work presents a GPS-free localisation method consisting of four stages that are executed only once during the network initialisation process. These stages are aimed to increase the overall system lifetime by reducing the signalling overhead commonly involved in distributed localisation procedures. The proposed localisation method turns the initial and complex node deployment to several smaller instances by dividing the network into clusters, which can be solved simultaneously based on local resources only. Simulation results show that this approach produces important savings in the involved overall complexity, which can translate into a trade-off between computational cost and localisation accuracy.