Error beacon filtering algorithm based on K-means clustering for underwater Wireless Sensor Networks

Due to the highly hostile and unpredictable underwater environments, some beacon nodes in Underwater Wireless Sensor Networks (UWSNs) tend to move or be damaged. Therefore, the unknown nodes will be positioned with larger error, which abases the value of data collected by sensor nodes. In order to solve the beacon error problem, this paper proposes an error beacon filtering algorithm based on K-means clustering. Firstly, the position of each beacon is calculated by an improved trilateration method, and then the beacon with the maximum positioning error is filtered out through K-means clustering algorithm. Simulation results suggest that this algorithm can detect almost all error beacons effectively.