Next Article in Journal
Acoustic Sensing and Ultrasonic Drug Delivery in Multimodal Theranostic Capsule Endoscopy
Next Article in Special Issue
Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks
Previous Article in Journal
A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction
Previous Article in Special Issue
A Reliable Data Transmission Model for IEEE 802.15.4e Enabled Wireless Sensor Network under WiFi Interference
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(7), 1554;

Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks

College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA
Merchant Marine College, Shanghai Maritime University, Shanghai 201306, China
Author to whom correspondence should be addressed.
Received: 4 April 2017 / Revised: 22 June 2017 / Accepted: 29 June 2017 / Published: 3 July 2017
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
Full-Text   |   PDF [2557 KB, uploaded 4 July 2017]   |  


Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes’ energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs’ election, we take nodes’ energies, nodes’ degree and neighbor nodes’ residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks. View Full-Text
Keywords: non-uniform distribution; distributed clustering; load balance; TSK fuzzy model; neighbor nodes’ energy non-uniform distribution; distributed clustering; load balance; TSK fuzzy model; neighbor nodes’ energy

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).

Share & Cite This Article

MDPI and ACS Style

Zhang, Y.; Wang, J.; Han, D.; Wu, H.; Zhou, R. Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks. Sensors 2017, 17, 1554.

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



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