Localization in Wireless Sensor Network Using MDS

In this paper, determining the localization of nodes in a Wireless Sensor Network is a very important task, which involves collaboration between sensor nodes. Localization is a fundamental service since it is relevant to many applications and to the network main functions, such as: routing, communication, cluster creation, network coverage, etc. Collaboration is essential to self-localization, so that localization can be accomplished by the nodes themselves, without any human intervention. In this paper, we first analyze the key aspects that have to be considered when designing or choosing a solution for the localization problem. Then, we present MDS localization algorithm. With this analysis of results simulated. We identified the results in topologies by taking different cases and we have addresses shortcomings, which are caused by anisotropic network topology and complex terrain, of existing sensor positioning methods. Then, we explore the idea of using multidimensional scaling technique to compute relative positions of sensors in a wireless sensor network. A distributed sensor positioning method based on multidimensional scaling is proposed to get the accurate position estimation and reduce error cumulation. Comparing with other positioning methods, with very few anchors, our approach can accurately estimate the sensors’ positions in network with anisotropic topology and complex terrain as well as eliminate measurement error cumulation. We also propose an on demand position estimation method based on multidimensional scaling for one or several adjacent sensors positioning. Experimental results indicate that our distributed method for sensor position estimation is very effective and