Next Article in Journal
Reagent-Less and Robust Biosensor for Direct Determination of Lactate in Food Samples
Next Article in Special Issue
Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring
Previous Article in Journal
Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks
Previous Article in Special Issue
A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(1), 141; doi:10.3390/s17010141

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

1
Key Laboratory of Networked Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem Information and Technology, Chinese Academy of Sciences, Shanghai 200050, China
4
Shanghai Research Center for Wireless Communications, Shanghai 201210, China
This is an expanded version of Wang, Z.-W.; Zeng, P.; Zhou, M.-T.; Li, D. Cluster-based maximum consensus time synchronization in IWSNs. In Proceedings of the IEEE 83rd Vehicular Technology Conference-Spring, Nanjing, China, 15–18 May 2016; pp. 1–5.
*
Author to whom correspondence should be addressed.
Academic Editors: Muhammad Imran, Athanasios V. Vasilakos, Thaier Hayajneh and Neal N. Xiong
Received: 24 November 2016 / Revised: 28 December 2016 / Accepted: 9 January 2017 / Published: 13 January 2017
(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)
View Full-Text   |   Download PDF [614 KB, uploaded 13 January 2017]   |  

Abstract

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs’ demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays. View Full-Text
Keywords: time synchronization; convergence rate; industrial wireless sensor networks; maximum consensus; communication delays time synchronization; convergence rate; industrial wireless sensor networks; maximum consensus; communication delays
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wang, Z.; Zeng, P.; Zhou, M.; Li, D.; Wang, J. Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks. Sensors 2017, 17, 141.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top