HRTS: A Hierarchical Reactive Time Synchronization Protocol for Wireless Sensor Networks

Precision time synchronization provides essential services for wireless ad hoc networks, which are required for applications such as communication, positioning and power management. Precision frequency synchronization not only plays an important role in improving the accuracy and energy efficiency of time synchronization, but also greatly improves the data reliability and communication quality. This paper proposes a precision time and frequency joint synchronization protocol, combining time synchronization with frequency synchronization. The two-stage protocol, consisting of coarse and fine synchronization, obtains improvements in accuracy, energy efficiency and time continuity. Experiments validate the correctness and feasibility of the proposed protocol, obtaining timing accuracy of 17.4 ns with standard deviation 6.61 ns and frequency accuracy within 0.3Hz for 128MHz clock.

The objective of Synchronization In wireless sensor network is to synchronize the various sensor nodes which are distributed as well as moving in a network. Synchronization is an important problem in communication networks especially for real time applications. There may be one base station of 1000 sensor nodes moving in the network. Synchronization is considered a particularly difficult in wireless sensor networks due to its decentralized structure. Synchronization can be done in different layers of the ISO model. The proposed study is about how to search the sensor nodes and synchronize them with smallest time. Recent advances in technology have made low cost, low power wireless sensors a reality. The proposed technique does not introduce collisions between synchronization messages, nor does it require costly digital signatures. Recent advances in miniaturization and low-cost, low power design have led to active research in large-scale networks of small, wireless, lowpower sensors and actuators.

Time synchronization is critical to sensor networks at many layers of its design and enables better duty-cycling of the radio, accurate localization, beamforming and other collaborative signal processing. While there has been significant work in sensor network synchronization, measurement based studies have been restricted to very short-term (few minutes) datasets and have focused on obtaining accurate instantaneous synchronization. Long-term synchronization has typically been handled by periodic re-synchronization schemes with beacon intervals of a few minutes based on the assumption that long-term drift is too hard to model and predict. Thus, none of this work exploits the temporally correlated behavior of the clock drift. Yet, there are incredible energy gains to be achieved from better modeling and prediction of long-term drift that can provide bounds on long-term synchronization error across a sensor network. Better synchronization can lead to significantly lower duty-cycles of the radio, simplify signal processing and can enable an order of magnitude greater lifetime than current techniques.We measure, evaluate and analyze in-depth the long-term behavior of synchronization skew and drift on typical Mica sensor nodes and develop an efficient long-term time synchronization protocol. We use four real time data sets gathered over periods of 12-30 hours in different environmental conditions to study the interplay between three key parameters that influence long-term synchronization - synchronization rate, history of past synchronization beacons and the estimation scheme. We use this measurement-based study to design an online adaptive time-synchronization algorithm that can adapt to changing clock drift and environmental conditions while achieving application-specified precision with very high probability. We find that our algorithm achieves between one and two orders of magnitude improvement in energy efficiency over currently available time-synchronization approaches.

A series of challenges exist in the process of sensor network research which can not be solved by one sensor node. Cooperative communication, based on the idea of spatial diversity, which makes different users or nodes in wireless network share their antennas or other network resources, is a promising technique toward improving performance of wireless sensor network significantly. This article adopts cooperation between nodes and opportunistic collaboration transmission strategy is proposed. Energy efficient power allocation algorithm in wireless sensor network is put forward to optimize performance of opportunistic cooperative transmission. Through the simulation, regardless of statistical feature of channel state of opportunistic node, opportunistic cooperation can effectively improve the performance of the system. Using energy efficient power allocation algorithm can effectively reduce energy consumption of the network and improve the network performance

Time synchronization is a significant component in Wireless Sensor Networks (WSNs) for maintaining synchrony among nodes. Most time synchronization protocols in WSNs utilize dedicated synchronization packets for clock accuracy optimization. However, in practical WSNs, the joint design of time synchronization and Media Access Control layer protocols should be considered. One approach is adding timestamps directly into data packets and the corresponding acknowledgements (ACKs). Therefore, communication and energy overhead could be saved greatly and time synchronization could be seamlessly integrated into networks. In this letter, we investigate the time synchronization scheme of listening nodes overhearing the neighboring two-way timing packet exchange based on periodical ACK mechanism and present an efficient clock skew estimation algorithm with clock correction upon every synchronization. The Maximum Likelihood Estimator (MLE) of clock skew for Gaussian random packet delay is derived, and the corresponding Cramer-Rao Lower Bound (CRLB) is obtained. In addition, the MLE shows that the clock skew could be estimated without any prior knowledge of the fixed packet delay and the time of adjustment. Simulation results verify that the MLE is efficient.

Most wireless sensor networks (WSNs) employ a sleep clock to enable sensor on-off mode to save energy. Since the sleep clock usually works at a relatively low frequency, it is important to correct the long-term synchronization error caused by instability and nonlinearity. In this paper, the time synchronization issue in a WSN is formulated as a closed-loop control problem. Using the proportional-integral (PI) control principle, we propose a feedback-based synchronization (FBS) scheme to compensate the clock drift caused by both internal perturbation and external disturbance. Synchronization accuracy and FBS dynamics are analyzed in terms of response time and overshoot. We also derive a formula to determine the controller parameters for different synchronization accuracy and response-time requirements. Extensive experiments have been conducted to evaluate this synchronization scheme. The results indicate that FBS is much more robust than the delay measurement time-synchronization (DMTS) protocol in different synchronization durations and sensor node configurations. It is shown that FBS achieves almost the same accuracy as the flooding time-synchronization protocol (FTSP) when synchronization period P is less than 60 s, and it outperforms FTSP when P is longer than 60 s. Furthermore, the experimental results reveal that FBS's response to an external disturbance is faster than that of FTSP in one- or two-hop WSN scenarios. In addition, FBS consumes fewer resources than FTSP.

Existing time synchronization schemes in sensor networks were all developed to be energy-efficient, precise, and robust, but none of them were developed with security in mind. We have developed a secure, accurate and energy-efficient time synchronization protocol (SAEP). SAEP achieves accurate time synchronization service with significantly reducing the number of message exchanges. Also, it safeguards against Byzantine failure, in which nodes drop, modify, or delay time information in an attempt to disrupt the time synchronization service in multi-hop networks. SAEP takes a distributed approach where each sensor independently makes decisions based only on the information collected from multiple adjacent nodes, thus achieving a high level of resistance to various attacks while minimizing the energy cost. We investigate the misbehavior of a maliciously compromised node and analyze how SAEP can combat these attacks. In our experiment SAEP outperforms the existing time synchronization protocol in accuracy, energy consumption and it is even resilient to multiple capture attacks.

Efficient and accurate time synchronization is critical to various applications in the Internet of Things and has been extensively studied. The emergence of large-scale, duty-cycled sensor networks ruins the previous assumptions used for protocol design, leading to the necessity of developing new synchronization protocols to achieve better energy efficiency and reliability. In this paper, the correlation-based time synchronization protocol (CorTiS), which exploits the spatiotemporal correlation between clocks, is developed. To the best of our knowledge, this is the first effort that exploits spatiotemporal correlation for time synchronization. A theoretical spatiotemporal model is presented to capture the collective behaviors of clocks. With this model, a probabilistic prediction scheme to infer synchronization errors based on correlation is developed without additional message exchanges. The CorTiS protocol is then developed incorporating community detection technique to cluster clocks that are tightly correlated as synchronization communities, such that different communities can be adaptively synchronized. Simulation results show that with CorTiS, participating nodes in each synchronization round can be significantly reduced in dynamic environments.

ABSTRACTThe clock in embedded systems usually is driven by a crystal oscillator and implemented via a counter register, such a crystal clock is non-identical and drifting due to the manufacturing tolerance and variation of working conditions. Thus, a common time among distributed wireless sensor nodes, also referred to as Time Synchronization, is required for many time-sensitive wireless applications, such as collaborative condition monitoring, coordinated control and localization. Inspired by fireflies’ behaviour, the Pulse-Coupled Oscillators (PCO) has been proposed for synchronization in complex networks. Since the concurrent transmission of PCO’s Pulses is impossible in Wireless Sensor Networks (WSNs), the desynchronization mechanism is adopted to ensure the implementation of PCO in WSNs. Moreover, due to the uncertainties in radio channels and the complexities of communication protocols and packet-exchange behaviours in wireless networks, it is challenging to have a closed-form solution to the performance of PCO synchronization in WSNs. The realistic software simulation, in particular, the discrete event simulator has been a powerful tool to exam the performance of communication protocols in various scenarios, since an order sequence of well-defined event in time is to represent the behaviour of a complex system. This paper presents the development of a pulse-coupled oscillators time synchronization simulator on the OMNeT++ platform for simulating and studying its behaviour and performance in sensor networks. A clock module with configurable phase and frequency noises, and adjustable and higher resolution is developed to mimic various crystal oscillators in embedded systems, for example, the real-time clock. The developed simulator also supports the full functions devices defined by ZigBee protocol, which allows realistic simulation of multi-hop IEEE 802.15.4 wireless networks. Finally, the intensive simulations of classical PCO with the refractory period in IEEE 802.15.4-based WSNs have been carried out to demonstrate the features and benefits of the developed simulator. It is shown that for the non-identical and time-varying PCO clocks in the WSNs, the achieved synchronization will lose gradually, and the time that maintained synchronization depends on the length of refractory period.

The performance of wireless sensor networks in terms of coverage, connectivity, lifetime and robustness is greatly influenced by the initial physical placement of the sensor nodes. In this paper we propose a novel deployment method for sensor nodes, when a large number of nodes is distributed from the air in a monitoring region that is inaccessible from the ground. In our deployment method, each sensor node is equipped with a parachute and a device to switch between its two falling behaviours (gliding and falling) in the air. After being dropped from midair, sensor nodes stochastically coordinate their falling behaviour in order to distribute themselves uniformly in the monitoring region. In addition, each sensor node exchanges messages with neighbouring nodes while being airborne and it changes its falling behaviour according to the density of the neighbouring nodes in order to reduce non-uniform areas. Through simulation evaluations, we confirm that our proposal can achieve a high uniformity in the placement of the nodes compared to a traditional airdrop method.

White-box switches have emerged as a pivotal component in modern networking architectures due to their flexibility, cost-effectiveness, and programmability. Within a data center network, achieving precise time synchronization within these switches is imperative for various critical functions such as packet scheduling, network security, and compliance with regulatory requirements. Conventional time synchronization protocols, like the Network Time Protocol (NTP), fail to meet the stringent time synchronization demands of the white-box switches because they are software-based. In contrast, the Precision Time Protocol (PTP), a hardware-based solution, offers sub-microsecond accuracy and low-latency time synchronization. However, despite the advantages of PTP, integrating it into white-box switches may pose challenges due to additional hardware requirements. This paper elaborates on a study conducted to understand the role of white-box switches and their precise time synchronization in data center networking, as well as a comparative measurement between NTP and PTP. Ultimately, this research contributes to a nuanced understanding of the role of PTP in modern white-box switches and lays down decision making processes regarding time synchronization protocols in networking deployments.

The ever-increasing number of WSN deployments based on a large number of battery-powered, low-cost sensor nodes, which are limited in their computing and power resources, puts the focus of WSN time synchronization research on three major aspects, i.e., accuracy, energy consumption and computational complexity. In the literature, the latter two aspects have not received much attention compared to the accuracy of WSN time synchronization. Especially in multi-hop WSNs, intermediate gateway nodes are overloaded with tasks for not only relaying messages but also a variety of computations for their offspring nodes as well as themselves. Therefore, not only minimizing the energy consumption but also lowering the computational complexity while maintaining the synchronization accuracy is crucial to the design of time synchronization schemes for resource-constrained sensor nodes. In this paper, focusing on the three aspects of WSN time synchronization, we introduce a framework of reverse asymmetric time synchronization for resource-constrained multi-hop WSNs and propose a beaconless energy-efficient time synchronization scheme based on reverse one-way message dissemination. Experimental results with a WSN testbed based on TelosB motes running TinyOS demonstrate that the proposed scheme conserves up to 95% energy consumption compared to the flooding time synchronization protocol while achieving microsecond-level synchronization accuracy.

In order to avoid clock skew in WSN (Wireless Sensor Networks) for large-scale photovoltaic modules monitoring, an improved time synchronization algorithm, TSP-GDM (Time Synchronization Protocol with Gaussian Delay Model) is proposed in this paper. Interdependence of local time stamps is established between network nodes according to a linear clock model. Local exchange and share of local time stamps in nodes are achieved by means of wireless transmission. An estimation method with the Gaussian Delay Model is designed to deal with the estimation problems of the node clock offset. The synchronization accuracy of the proposed method is verified with the MATLAB simulation. It is found that TSP-GDM can be applied to synchronous topology of large-scale photovoltaic modules monitoring with a higher synchronization accuracy. Compared to RBS (Reference Broadcast Synchronization), TPSN (Timing-synchronization Protocol for Sensor Networks) and RTSP (Recursive Time-Sync Protocol for WSN), its synchronization accuracy in an inner layer has been increased by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$22.57~\mu \text{s}$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$15.7~\mu \text{s}$ </tex-math></inline-formula> and 4.26 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> respectively.

Single twisted pair Ethernet becomes popular in the industrial internet of thing (IIoT), since it can use only one twisted pair to provide high speed data transmission while the cables of the field bus can be reused. However, since its transmission medium is inferior to traditional Ethernet, it is easier to generate delay jitter that greatly impacts the accuracy of time synchronization. To solve this problem, in this paper, an offset estimation method based on AutoRegressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) is proposed to estimate the clock offset when the delay jitter appears. The offset estimation model is firstly obtained by training the ARIMA-LSTM with offline offset data. When the delay jitter is detected, the offset can be estimated by the model to replace the unreliable offset obtained by the time synchronization protocol. Experiments are executed in the testbed, and the results prove that the proposed method can improve the time synchronization accuracy in the single twisted pair Ethernet.

Wireless networking is a crucial component of communication in this era of digitization. The key characteristics that determine a wireless network's performance are smooth connectivity, quicker communication, and increased customer satisfaction. Scalability deals with the erratic workload and new resources that are added to the network. Scalability is crucial for both Quality of Experience (QoE) and Quality of Service (QoS) in such a power-constrained environment because wireless devices are battery-operated. Managing power consumption and network performance simultaneously in scalable networking scenario is quite challenging, especially during handover. This research proposed a methodology to assess the impact of scalability on wireless node power consumption and network performance in order to develop energy-efficient handoff mechanisms. The Type-I and Type-II wireless node sets were used between the WiFI and WiMAX networks in a vertical handover scenario. In the study, two distinct scalability scenarios were taken into account. Three distinct voltage levels—cutoff voltage, nominal voltage, and charge voltage —had been used to examine the consumption of power. Throughput, residual energy, and Packet Delivery Ratio (PDR) were computed to examine the network's performance in a scalable, power-constrained context. Two different scalability scenarios were considered in the study. The power consumption was investigated using three different voltage levels: charge voltage, nominal voltage, and cutoff voltage. The network's performance under scalable, power-constrained conditions was investigated by computing throughput, packet delivery ratio (PDR), and residual energy. The result obtained in the study showed the variation in battery drainage of wireless nodes under the effect of various scalability factors. This study will provide a blueprint for developing novel algorithms which eventually will improvise network performance and strengthen the base of Green Networking.