Research On MDS-based Localization Algorithm Of Wireless Sensor Networks

There are many applications of wireless sensor networks, location information has taken an increasingly important seat. The general way to obtain location information is either to set up manually or to install GPS. Prior to deploying sensors, manual setting will waste a vast amount of time and human resources. A better way to get location information is to use the localization algorithm.Multidimensional scaling (MDS) is a data analysis technique that transforms proximity information into geometric information. MDS is well-suited to node localization in communication networks, where the task is to use the distance information between nodes to determine the coordinates of nodes in a 2D or 3D space. Localization approaches based on MDS could work efficiently in wireless sensor networks, so this dissertation focuses on it.First of all, based on the study of plenty of related literatures, characteristic of wireless sensor networks, current research status of location algorithms and systems for wireless sensor networks are summarized. The categories of recent representative localization approaches are discussed.Then, in this dissertation we give details of a simple mathematical technique, classical multidimensional scaling and how it solves the location problem. This dissertation presents EMDS-MAP (P) algorithm from based on discussion of problems of MDS algorithm, which through Euclidean algorithm to get Euclidean distance between the two-hop neighbor nodes. Obviously, this will effectively reduce positioning error which is introduced by the distance matrix, thereby improve positioning accuracy.Finally, we compared our work with MDS-MAP (P) via simulation. It is demonstrated that the proposed algorithm has higher accuracy, low computation and algorithm complexity features.