A robust localization algorithm in wireless sensor networks

Most of the state-of-the-art localization algorithms in wireless sensor networks (WSNs) are vulnerable to various kinds of location attacks, whereas secure localization schemes proposed so far are too complex to apply to power constrainedWSNs. This paper provides a distributed robust localization algorithm called Bilateration that employs a unified way to deal with all kinds of location attacks as well as other kinds of information distortion caused by node malfunction or abnormal environmental noise. Bilateration directly calculates two candidate positions for every two heard anchors, and then uses the average of a maximum set of close-by candidate positions as the location estimation. The basic idea behind Bilateration is that candidate positions calculated from reasonable (i.e., error bounded) anchor positions and distance measurements tend to be close to each other, whereas candidate positions calculated from false anchor positions or distance measurements are highly unlikely to be close to each other if false information are not collaborated. By using ilateration instead of classical multilateration to compute location estimation, Bilateration requires much lower computational complexity, yet still retains the same localization accuracy. This paper also evaluates and compares Bilateration with three multilateration-based localization algorithms, and the simulation results show that Bilateration achieves the best comprehensive performance and is more suitable to real wireless sensor networks.