Localization

Localization is the fundamental for many applications in wireless sensor networks. To date, there exists two major methods to achieve localization, namely the centralized localization method and the distributed localization method. However, the centralized localization method will cause big error, while in distributed localization method, location of each node needs to be calculated, and the order of complexity is high.Therefor, we propose a cluster method based on max connectivity and multi-border nodes.

Approach

We approach a new cluster method based on the maximum connection and the common nodes of neighbor clusters. Each node can obtain its intra-cluster localization via any methods such as MDS(Multidimensional Scaling), and the neighbor cluster patch together based on the common nodes' intra-cluster localization information. Then the small local maps expand to global map. In this way, we can know the positions of all the nodes.

Systems/Experiments

We verified our cluster and localization method by simulation.The simulation results showed that the order of complexity of the localization method is low, and the localization error is similar to the distributed method MDS-MAP(P).

Accomplishments

In May 2008, our paper about the localization method was accepted by the High Technology Letters（Chinese）.

Future Directions

We plan to implement our cluster method and localization method in our Sensor Network platform: EasiNet, and try to consummate our cluster method.