Belief-Based Cleaning in Trajectory Sensor Streams
The imprecision in data streams received at the base station is common in mobile wireless sensor networks. The movement of sensors leads to dynamic spatio-temporal relationships among sensors and invalidates the data cleaning techniques designed for stationary networks. As one of the first methods designed for mobile environments, the authors introduce a novel online method to clean the imprecise or dirty data in mobile wireless sensor networks. Their method deploys a belief parameter to select the helpful neighboring sensors to clean data. The belief parameter is based on sensor trajectories and the consistency of their streaming data correctly received at the base station.