On the practical implementation of propagation delay and clock skew compensated high-precision time synchronization schemes with resource-constrained sensor nodes in multi-hop wireless sensor networks

Wireless sensor networks (WSNs) of spatially distributed autonomous sensors are used to monitor physical or environmental conditions such as temperature, sound, pressure, etc. They are also used to cooperatively pass the collected data through the network to a main location. Due to the application of wireless sensor networks as a monitoring device in the real world, the physical time of the occurrence of events is important. Since WSNs have particular constraints and limitations, synchronizing the physical times for these networks is considered to be a complex task. Although many algorithms have been proposed for synchronizing time in the network, there are two main error factors in all the proposed algorithms. The first factor is the clock drift which might be caused by the influence of different environmental factors such as temperature, ambient temperature, humidity, it might be generated on crystal oscillator which is inevitable The second error factor is indeterminacy which is attributed to the existence of non-deterministic delays in sending and receiving messages between sensor nodes. These two factors together reduce the precision of synchronization algorithms. In this paper, the researchers proposed a new approach for dealing with the above-mentioned two problems and achieving better synchronization. The proposed approach is a combination of flooding time synchronization protocol (FTSP) and reference broadcast synchronization (RBS).This approach is intended to increase synchronization accuracy and network lifetime by reducing the number of synchronization messages sent between nodes and eliminating the most of non-deterministic errors in sending messages. The results of simulations conducted in the study indicated that the proposed approach is significantly more efficient than the FTSP and RBS methods in terms of parameters such as accurate synchronization, amount of sent packets and power consumption.

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Realtime Clock Skew Estimator for Time Synchronization in Wireless Sensor Networks of WUSB and WBAN

Journal of Korea Multimedia Society ◽

10.9717/kmms.2012.15.11.1391 ◽

2012 ◽

Vol 15 (11) ◽

pp. 1391-1398

Author(s):

Kyeong Hur

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Time Synchronization ◽

Wireless Sensor ◽

Clock Skew

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Clock Drift Management Using Nature Inspired Algorithms

Journal of Information Technology Research ◽

10.4018/jitr.2012100104 ◽

2012 ◽

Vol 5 (4) ◽

pp. 48-62

Author(s):

Prakash Tekchandani ◽

Aditya Trivedi

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Time Synchronization ◽

Synchronization Error ◽

Wireless Sensor ◽

Clock Skew ◽

Clock Drift ◽

Distributed Sensor ◽

Network Applications ◽

Nature Inspired Algorithms

Time Synchronization is common requirement for most network applications. It is particularly essential in a Wireless Sensor Networks (WSNs) to allow collective signal processing, proper correlation of diverse measurements taken from a set of distributed sensor elements and for an efficient sharing of the communication channel. The Flooding Time Synchronization Protocol (FTSP) was developed explicitly for time synchronization of wireless sensor networks. In this paper, we optimized FTSP for clock drift management using Particle Swarm Optimization (PSO), Variant of PSO and Differential Evolution (DE). The paper estimates the clock offset, clock skew, generates linear line and optimizes the value of average time synchronization error using PSO, Variant of PSO and DE. In this paper we present implementation and experimental results that produces reduced average time synchronization error using PSO, Variant of PSO and DE, compared to that of linear regression used in FTSP.

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Node-Identification-Based Secure Time Synchronization in Industrial Wireless Sensor Networks

Sensors ◽

10.3390/s18082718 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2718 ◽

Cited By ~ 5

Author(s):

Zhaowei Wang ◽

Peng Zeng ◽

Linghe Kong ◽

Dong Li ◽

Xi Jin

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Time Synchronization ◽

Information Filtering ◽

Algorithm Design ◽

Main Idea ◽

Wireless Sensor ◽

Clock Skew ◽

Industrial Wireless Sensor Networks ◽

Sybil Attacks

Time synchronization is critical for wireless sensors networks in industrial automation, e.g., event detection and process control of industrial plants and equipment need a common time reference. However, cyber-physical attacks are enormous threats causing synchronization protocols to fail. This paper studies the algorithm design and analysis in secure time synchronization for resource-constrained industrial wireless sensor networks under Sybil attacks, which cannot be well addressed by existing methods. A node-identification-based secure time synchronization (NiSTS) protocol is proposed. The main idea of this protocol is to utilize the timestamp correlation among different nodes and the uniqueness of a node’s clock skew to detect invalid information rather than isolating suspicious nodes. In the detection process, each node takes the relative skew with respect to its public neighbor as the basis to determine whether the information is reliable and to filter invalid information. The information filtering mechanism renders NiSTS resistant to Sybil attacks and message manipulation attacks. As a completely distributed protocol, NiSTS is not sensitive to the number of Sybil attackers. Extensive simulations were conducted to demonstrate the efficiency of NiSTS and compare it with existing protocols.

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Pair Nodes Clock Synchronization Algorithm Based on Kalman Filter for Underwater Wireless Sensor Networks

Sensors ◽

10.3390/s21134426 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4426

Author(s):

Xiaomeng Ni ◽

Ting Lu ◽

Sijia Ye ◽

Yunsi Zheng ◽

Pengfei Chen ◽

...

Keyword(s):

Wireless Sensor Networks ◽

Kalman Filter ◽

Sensor Networks ◽

Time Synchronization ◽

Clock Synchronization ◽

Wireless Sensor ◽

Underwater Wireless Sensor Networks ◽

Clock Skew ◽

Time Stamps ◽

Clock Offset

Time synchronization is the basis of many applications. Aiming at the limitations of the existing clock synchronization algorithms in underwater wireless sensor networks, we propose a pairwise synchronization algorithm called K-Sync, which is based on the Kalman filter. The algorithm does not need the assistance of the position sensor or the speed sensor, and the high time synchronization accuracy can be realized only by utilizing the time-stamps information in the process of message exchange. The K-Sync uses the general constraints of the motion characteristics of the sensor nodes to establish the recursive equations of the clock skew, clock offset, relative mobility velocity, and relative distance. At the same time, the time-stamps are viewed as the observation variables and the system observation equation is obtained. The K-Sync estimates the normalized clock skew and offset of the node via the Kalman filter to achieve high-precision clock synchronization between the two nodes. The simulation shows that the K-Sync has obvious advantages in the key indicators such as the estimated accuracy of clock skew and clock offset, convergence speed, etc. In addition, the K-Sync is more robust to a variety of underwater motion scenes.

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Measurements Used in Wireless Sensor Networks Localization

Localization Algorithms and Strategies for Wireless Sensor Networks ◽

10.4018/978-1-60566-396-8.ch002 ◽

2009 ◽

pp. 33-53

Author(s):

Fredrik Gustafsson ◽

Fredrik Gunnarsson

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Network Architecture ◽

Time Synchronization ◽

Sensor Nodes ◽

Wireless Sensor ◽

Time Of Arrival ◽

General Observation ◽

Network Nodes ◽

Sonic Wave

Wireless sensor networks (WSN) localization relies on measurements. Availability of, and the information content in, these measurements depend on the network architecture, connectivity, node time synchronization and the signaling bandwidth between the sensor nodes. This chapter addresses wireless sensor networks measurements in a general framework based on a set of nodes, where each node either emits or receives signals. The emitted signal can for example be a radio, acoustic, seismic, infrared or sonic wave that is propagated in a certain media to the receiver. This general observation model does not make any difference between localization of sensor network nodes or unknown objects, or whether the nodes or objects are stationary or mobile. The information available for localization in wireless cellular networks (WCN) is in literature classified as direction of arrival (DOA), time of arrival (TOA), time difference of arrival (TDOA) and received signal strength (RSS). This chapter generalizes these concepts to the more general wireless sensor networks.

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Mobile target localization based on iterative tracing for underwater wireless sensor networks

International Journal of Distributed Sensor Networks ◽

10.1177/1550147720940634 ◽

2020 ◽

Vol 16 (7) ◽

pp. 155014772094063

Author(s):

Ruolin Guo ◽

Danyang Qin ◽

Min Zhao ◽

Guangchao Xu

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Acoustic Waves ◽

Propagation Delay ◽

Target Localization ◽

Sensor Nodes ◽

Wireless Sensor ◽

Underwater Wireless Sensor Networks ◽

Underwater Environment ◽

Mobile Target

In underwater wireless sensor networks, sensor position information has important value in network protocols and collaborative detection. However, many challenges were introduced in positioning sensor nodes due to the complexity of the underwater environment. Aiming at the problem of the stratification effect of underwater acoustic waves, the long propagation delay of messages, as well as the mobility of sensor nodes, a mobile target localization scheme for underwater wireless sensor network is proposed based on iterative tracing. Four modules are established in the mobile target localization based on iterative tracing: the data collection and rough position estimation, the estimation and compensation of propagation delay, the node localization, and the iteration. The deviation of distance estimation due to the assumption that acoustic waves propagate along straight lines in an underwater environment is compensated by the mobile target localization based on iterative tracing, and weighted least squares estimation method is used to perform linear regression. Moreover, an interacting multiple model algorithm is put forward to reduce the positioning error caused by the mobility of sensor nodes, and the two services of node time synchronization and localization assist each other during the iteration to improve the accuracy of both parties. The simulation results show that the proposed scheme can achieve higher localization accuracy than the similar schemes, and the positioning errors caused by the above three problems can be reduced effectively.

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