Drift estimation using pairwise slope with minimum variance in wireless sensor networks

Time synchronization is mandatory for applications and services in wireless sensor networks which demand common notion of time. If synchronization to stable time sources such as Coordinated Universal Time(UTC) is required, employing the method of flooding in order to provide time synchronization becomes crucial. In flooding based time synchronization protocols, current time information of a reference node is periodically flooded into the network. Sensor nodes collect the time information of the reference node and perform least-squares regression in order to estimate the reference time. However, least-squares regression exhibits a poor performance since sensor nodes far away from the reference node collect the time information with large deviations. Due to this fact, the slopes of their least-squares line exhibit large errors and instabilities. As a consequence, the reference time estimates of these nodes also exhibit large errors.