Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

The sensor nodes in the Wireless Sensor Networks (WSNs) are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applyi...

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Published inMathematical problems in engineering Vol. 2014; no. 1
Main Authors Huang, Yuanjiang, Martínez, José-Fernán, Hernández Díaz, Vicente, Sendra, Juana
Format Journal Article
LanguageEnglish
Published New York Hindawi Publishing Corporation 01.01.2014
John Wiley & Sons, Inc
Subjects
Algorithms
Battery
Binomial distribution
Controllers
Design
Embedded systems
Failure
Fault tolerance
Fuzzy control
Fuzzy logic
Fuzzy sets
Mathematical analysis
Mathematical models
Network topologies
Networks
Neural networks
Nodes
Remote sensors
Topology
Wireless networks
Wireless sensor networks
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Summary:The sensor nodes in the Wireless Sensor Networks (WSNs) are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC), of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC), of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE) through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.
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ISSN:1024-123X
1563-5147
DOI:10.1155/2014/973163