scholarly journals Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 141 ◽  
Author(s):  
Zhaowei Wang ◽  
Peng Zeng ◽  
Mingtuo Zhou ◽  
Dong Li ◽  
Jintao Wang
Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2718 ◽  
Author(s):  
Zhaowei Wang ◽  
Peng Zeng ◽  
Linghe Kong ◽  
Dong Li ◽  
Xi Jin

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.


2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Niranjan Panigrahi ◽  
Pabitra Mohan Khilar

Wireless Sensor Networks (WSNs)  have received considerable attention in recent years because of its broad area of applications. In the same breadth, it also faces many challenges. Time synchronization is one of those fundamental challenges faced by WSN being a distributed system. Several approaches have been proposed in the last decade for time synchronization in WSNs. Recently, Consensus Time Synchronization (CTS) approaches are gaining popularity due its computational lightness, robustness and distributed nature. Though a rich set of CTS algorithms are proposed, their energy consumption has so far not been studied. Apart from synchronization precision, energy consumption should also be considered meticulously for time synchronization algorithms in energy-constraint WSNs. In this paper, a thorough energy consumption analysis is presented for some recent state-of-the-art CTS algorithms for WSN and tested by simulation. The simulation results will help in selecting an appropriate CTS algorithm that meets the requirements of synchronization accuracy and energy consumption for a specific WSN application.


2015 ◽  
Vol 15 (3) ◽  
pp. 1404-1413 ◽  
Author(s):  
Jie Wu ◽  
Liyi Zhang ◽  
Yu Bai ◽  
Yunshan Sun

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4095
Author(s):  
Mahmoud Elsharief ◽  
Mohamed A. Abd El-Gawad ◽  
Haneul Ko ◽  
Sangheon Pack

Time synchronization is an essential issue in industrial wireless sensor networks (IWSNs). It assists perfect coordinated communications among the sensor nodes to preserve battery power. Generally, time synchronization in IWSNs has two major aspects of energy consumption and accuracy. In the literature, the energy consumption has not received much attention in contrast to the accuracy. In this paper, focusing on the energy consumption aspect, we introduce an energy-efficient reference node selection (EERS) algorithm for time synchronization in IWSNs. It selects and schedules a minimal sequence of connected reference nodes that are responsible for spreading timing messages. EERS achieves energy consumption synchronization by reducing the number of transmitted messages among the sensor nodes. To evaluate the performance of EERS, we conducted extensive experiments with Arduino Nano RF sensors and revealed that EERS achieves considerably fewer messages than previous techniques, robust time synchronization (R-Sync), fast scheduling and accurate drift compensation for time synchronization (FADS), and low power scheduling for time synchronization protocols (LPSS). In addition, simulation results for a large sensor network of 450 nodes demonstrate that EERS reduces the whole number of transmitted messages by 52%, 30%, and 13% compared to R-Sync, FADS, and LPSS, respectively.


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