On the interaction of clocks, power, and synchronization in duty-cycled embedded sensor nodes

Abstract

The efficiency of the time synchronization service in wireless sensor networks is tightly connected to the design of the radio, the quality of the clocking hardware, and the synchronization algorithm employed. While improvements can be made on all levels of the system, over the last few years most work has focused on the algorithmic level to minimize message exchange and in radio architectures to provide accurate time-stamping mechanisms. Surprisingly, the influences of the underlying clock system and its impact on the overall synchronization accuracy has largely been unstudied.In this work, we investigate the impact of the clocking subsystem on the time synchronization service and address, in particular, the influence of changes in environmental temperature on clock drift in highly duty-cycled wireless sensor nodes. We also develop formulas that help the system architect choose the optimal resynchronization period to achieve a given synchronization accuracy. We find that the synchronization accuracy has a two region behavior. In the first region, the synchronization accuracy is limited by quantization error, while int he second region changes in environmental temperature impact the achievable accuracy. We verify our analytic results in simulation and real hardware experiments.

A Survey of Clock Synchronization Over Packet-Switched Networks

“…It is worth noting that the clock frequency accuracy is generally given in terms of parts-per million (ppm) or parts-per billion (ppb). A frequency error at given time t, f e (t) = f (t) − f 0 , corresponds to the difference between the measurement frequency f (t) and nominal frequency f 0 [7]. For example, an accuracy of 5 ppm means that the average clock frequency can differ by 5 Hz every 1 MHz of its given value.…”

“…Also, WSNs are bandwidth constrained compared to wired networks, and thus the synchronization traffic need to be limited. Furthermore, WSNs are generally duty cycled embedded systems, characterized by long sleep state intervals and short transmission state intervals [7]. In the following, we review the main synchronization protocols specifically proposed for WSNs, which can be categorized into static and dynamic protocols.…”

“…Temperature and manufacturing inaccuracies are the two most significant frequency error sources [7], [83]. Manufacturing imprecision is static over time, however temperature changes frequently and thus needs to be taken into account dynamically.…”

“…In Ganeriwal et al [84], part of the Roseline project, 7 proposed the Rate Adaptive Time Synchronization (RATS) which considers a set of timestamp samples in order to model a linear clock model. More specifically, using the timestamp samples, a prediction error E p is compared to a known application error bound E max .…”

Energy-Efficient Communication in Wireless Networks

“…In the case of the device, temperature efects and component selection have a signiicant efect on relative clock drift, which must be taken into account when tuning and learning protocol parameters like guard times and phase ofsets, respectively (Section 2). Understanding clock drift is essential to tightly conigure networking parameters, such as guard times to ensure accurate synchronisation, and has been studied in [25] where the authors investigate the efects of environmental temperature on clock drift and propose strategies to help designers choose optimal resynchronisation periods for given accuracies, and in [26] where the authors study the impact of oscillator drift on end-to-end latency over multiple hops using varying capacitor accuracies and show how to determine optimal parameters to minimise energy consumption in duty-cycled wireless sensor networks using low power medium access control techniques. It is also worth noting that temperature inluences batery performance, particularly as temperatures reduce, where capacity is degraded and voltage is known to reduce.…”