Recurrent Grid Based Voting Approach for Location Estimation in Wireless Sensor Networks

With the advent of location aware sensor applications, precise location discovery has become an important technology in wireless sensor networks. Inter Peer communication in the sensor network has been modeled as the graph with constraints defined in terms of proximity. Recurrent grid based voting approach (RGBV) has been introduced to estimate the location of unknown nodes in the network. Voting scheme is adopted on an iterative basis for the nodes. For each node, region of interest (ROI) with the maximum votes is figured out as the collection of two-dimensional points after recursive voting. Convex hull is generated from this set of points to frame the actual ROI. Additionally, minimum bounding rectangle algorithm has been applied to figure out the centroid of the region. The centroid thus estimated is the required location of unknown node. Our methodology is shown to have fast convergence with low estimation error, even for complex networks. The simulation results demonstrate that the proposed method is promising for the current generation of sensor networks.