Research On Node Localization Method In Wireless Sensor Networks Based On OMNeT++

In recent years, Wireless Sensor Networks(WSNs), which integrates wireless communication, distributed computing, micro-electromechanical system and so on, has developed rapidly and it has been expanded to many fields. It is one of the most basic requirements for nodes in WSNs to obtain their positions. So node localization is one of key problems and is the basis and prerequisite for practical applications of WSNs. Therefore, studying on node localization is of great importance both theoretically and practically for WSNs.Firstly, the characteristics and some novel research on WSNs is analysed in depth. Then the beacon selection optimization strategy in distributive multi-energy node localization algorithm is studied in this paper. This paper also studies the node localization problem in mobile WSNs based on Monte Carlo method. Finally, all the theories and algorithms are simulated with discrete event simulator called OMNeT++. The main work of the paper and research contributions are briefly summarized as follows:1) In order to overcome the high computational complexity problem in concentric anchor beacon localization algorithm, an anchor selection scheme is proposed. The proposed scheme can not only reduce algorithm complexity, but also improve the localization accuracy. The main idea of the algorithm is as following: Based on the network physical topology characteristics, only three anchors selected among all the neighboring. The selected anchors are used for node localization. What's more, the three beacons should be selected so that the sum of the distances between any two of them is the farthest among all possible combinations of neighbor beacons. The estimation location can be calculated based on centroid algorithm.2) The multi-energy idea is further introduced to address the problem of node localization in mobile sensor network. A localization algorithm based on Monte Carlo, which is suitable for mobile wireless sensor network is proposed in this paper. Each Mobile anchor emits beacon information at different power levels. From the information received by each unknown nodes, the sensor node can determine which particular ring or inner circle it lies within from the correspondent anchor, which is called constraint region. The positions of unknown nodes are able to be estimated by a bunch of particles which are sampled based on an improved Monte Carlo Localization scheme. In order to further enhance localization performance, the concept called Collinearity Limiting Factor (CLF) is introduced to avoid localization failure caused by beacon collineation. By using CLF, a beacon selection scheme is put forwarded to solve the beacon collineation problem.