An efficient fuzzy localization approach in Wireless Sensor Networks

A successful node localization is of great importance to design efficient localization algorithms in Wireless Sensor Networks (WSNs). A proper node deployment can assist in routing, data fusion and communication in large scale ad hoc networks. Furthermore, it can extend the lifetime of WSNs by minimizing energy consumption. In this paper, we propose range-free localization using Fuzzy logic to achieve a more optimum solution. We model edge weights using Fuzzy logic system, which utilize the current value of Received Signal Strength Indicator (RSSI) and the Link Quality Indicator (LQI) from the anchor nodes for deciding location of sensor nodes. We have implemented our approach as a TinyOS module, and evaluated it through extensive TOSSIM simulations. Simulation results have shown promising results and demonstrate the effectiveness of the proposed approach.

I. Introduction

WSNs is one of the potential emerging computing technologies, edging gradually from the concept stage to practical reality. Present day applications of WSN have been identified to monitor inhospitable environs of dynamic nature. Wireless sensor network can be deployed in various application rights from military, biomedical, and environmental utilization. The typical issues in wireless sensor networks like their limited energy and computational capability are being progressively addressed by newer research. Although there has been an extensive research work towards energy, it still remains a major obstruction towards development of the effective routing algorithm in wireless sensor networks. Wireless Sensor platforms are now carrying sensors ranging from acoustic, temperature, pressure, humidity and also video amongst other sensors. With the increasing complexity of data to be captured and transmitted, the networks have to evolve further with ability to retain energy and thereby life, transmit more complex and voluminous data and intelligently decide the most optimum direction for this data exchange. In each case, determining the location of wireless nodes is a very sensitive operation and is highly important in order to make measured data significant. Existing truth table based logic, as being advocated, would not suffice to accomplish this relatively complex network requirement. We propose to introduce Fuzzy logic in this scheme of things to achieve a more optimum solution in sensor nodes position estimation.