Conectivity based localization in wireless sensor networks

Abstract

Identifying the position of the sensor nodes is an important issue in the practical applications of wireless sensor networks (WSN). In the environment, there are many factors influencing to node position estimation, increasing the possibility of error rate. Localization in WSN helps to address the position of the sensor nodes. With the information from localization, there are many factors are explored such as energy map generation, node addressing or geographic routing. Therefore, localization is an important point leading to the success of WSN Localization can be achieved by two main techniques: range based and range free. With the advantages of higher accuracy and lower energy, Range-free is considered as efficient techniques to estimate node position due to bringing low cost and higher accuracy. In this study, we would like to focus on DV-Hop, an optimization in range free method using due to the pros of not depending on any influencing factors in the environment. We would like to apply two different algorithms to estimate the node positions from the measurements of DV-Hop: least square and particle swarm optimization (PSO). Using PSO in DV-Hop method, the conducted extensively simulation shows the positive impact of PSO in calculating hop count to identify nodes while using the small number of sample anchor nodes. The result also asserts that the error rate is improved when the number of anchors increased.