Energy-efficient localization for mobile sensor networks based on RSS and historical information

Existing localization algorithms for mobile sensor networks are mostly based on the Sequential Monte Carlo (SMC) localization method. However, these methods usually suffer from low sampling efficiency. So some algorithms try to reduce the sampling area by employing position relationship with neighbor common nodes. But such algorithms need high communication cost and significantly shorten the network life time. In order to solve the energy problem and improve localization accuracy, in this paper, we proposed a new energy-efficient algorithm based on Received Signal Strength (RSS), distance and direction of the moving anchor nodes and Monte Carlo localization (MCL), so the algorithm is called RDMCL. RDMCL derives three methods based on the number of nodes´ one-hop neighbor anchors to build a more effective sampling area. Simulation results show that our algorithm indeed improve localization accuracy and save energy cost of network.