Towards Adaptive Localization in Wireless Sensor Networks

It is often useful or even indispensable to know the locations of the nodes in a wireless sensor network (WSN), from both network functionality and applications point of view. A potential yet one of the most challenging method is to utilize received signal strength indicator (RSSI) for distance estimation. Albeit easily adopted, using of RSSI is notorious for imprecise distance estimates which can lead to inaccuracies in location estimates. In this paper, we study RSSI-based localization in WSNs through simulation experiments. We evaluate and compare a hybrid algorithm and its modifications with well-known range-based and range-free localization algorithms. Simulation results indicate that hybrid algorithms which adapt to varying conditions are more appropriate for RSSI-based localization on a broad scale. We could further improve the location accuracy of the studied hybrid algorithm(s) by applying a variant proposed by us. More importantly, it was observed that even better results could be achieved if each node were able to choose the most suitable algorithm individually. This kind of local adaptivity in localization seems a promising approach in diverse and dynamical environments, which are, for RSSI-based localization in particular, extremely challenging.