Enhancing Time Synchronization Support in Wireless Sensor Networks

Abstract

With the emerging Internet of Things (IoT) technology becoming reality, a number of applications are being proposed. Several of these applications are highly dependent on wireless sensor networks (WSN) to acquire data from the surrounding environment. In order to be really useful for most of applications, the acquired data must be coherent in terms of the time in which they are acquired, which implies that the entire sensor network presents a certain level of time synchronization. Moreover, to efficiently exchange and forward data, many communication protocols used in WSN rely also on time synchronization among the sensor nodes. Observing the importance in complying with this need for time synchronization, this work focuses on the second synchronization problem, proposing, implementing and testing a time synchronization service for low-power WSN using low frequency real-time clocks in each node. To implement this service, three algorithms based on different strategies are proposed: one based on an auto-correction approach, the second based on a prediction mechanism, while the third uses an analytical correction mechanism. Their goal is the same, i.e., to make the clocks of the sensor nodes converge as quickly as possible and then to keep them most similar as possible. This goal comes along with the requirement to keep low energy consumption. Differently from other works in the literature, the proposal here is independent of any specific protocol, i.e., it may be adapted to be used in different protocols. Moreover, it explores the minimum number of synchronization messages by means of a smart clock update strategy, allowing the trade-off between the desired level of synchronization and the associated energy consumption. Experimental results, which includes data acquired from simulations and testbed deployments, provide evidence of the success in meeting this goal, as well as providing means to compare these three approaches considering the best synchronization results and their costs in terms of energy consumption.

An Adaptive Fuzzy-PI Clock Servo Based on IEEE 1588 for Improving Time Synchronization Over Ethernet Networks

“…PTP implementation has also been considered in a wireless network. Tavares Bruscato et al [29] presented a method using an auto-correction approach, a prediction mechanism, and an analytical correction mechanism to enhance time synchronization support in wireless sensor networks. Yildirim et al [30], presented an adaptive PI clock servo for a wireless sensor network.…”

“…However, the latency and noise that occur during frame exchanges and quantization errors prevent the system time from reaching perfect synchronization. Therefore, filters have been attached to PI compensation, but they cause a time-constant delay before a component reaches the time error boundary [25]- [29]. That slows the initial processing phase of the system and causes lost packets.…”

Wireless Sensor Network Synchronization for Precision Agriculture Applications

“…One such challenge is the need for synchronization, which often comes up in networking environments, and especially so in distributed systems [12,13]. Network synchronization is required to provide time-correlated measurements from remote nodes, so that, when the time comes for the individual data to be processed or fused to compose a new set of information, the latter can be successfully interpreted by the end-user or application and utilized for the decision-making process [14]. Accurate synchronization can be difficult to achieve, due to multiple delays that can accumulate, depending on the utilized hardware and software, alike.…”

DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks

“…Numerous time synchronization protocols for terrestrial wireless sensor networks have been proposed in various publications, such as the fine-grained network time synchronization using reference broadcasts (RBS) [4], the timing-sync protocol for sensor networks (TPSN) [5], the flooding time synchronization protocol (FSTP) [6] and others [7,8,9,10]. However, these protocols cannot be directly applied to underwater sensor networks.…”