ACES: Adaptive Clock Estimation and Synchronization Using Kalman Filtering

Clock synchronization across a network is essential for a large number of applications ranging from wired network measurements to data fusion in sensor networks. Earlier techniques are either limited to undesirable accuracy or rely on specific hardware characteristics that may not be available for certain systems. In this work, we examine the clock synchronization problem in resource-constrained networks such as wireless sensor networks where nodes have limited energy and bandwidth, and also lack the high accuracy oscillators or programmable network interfaces some previous protocols depend on. This paper derives a general model for clock offset and skew and demonstrates its applicability. We design efficient algorithms based on this model to achieve high synchronization accuracy given limited resources. These algorithms apply the Kalman filter to track the clock offset and skew, and adaptively adjust the synchronization interval so that the desired error bounds axe achieved. We demonstrate the performance advantages of our schemes through extensive simulations obeying real-world constraints.