Fuzzy-based fault-tolerant low-energy adaptive clustering hierarchy routing protocol for wireless sensor network

2016 ◽  
Vol 11 (2) ◽  
pp. 117 ◽  
Author(s):  
Maya Shelke ◽  
Getenet Tefera ◽  
Akshay Malhotra ◽  
Parikshit Mahalle
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Fault Tolerant ◽  
Low Energy ◽  
Wireless Sensor ◽  
Adaptive Clustering

scholarly journals An Energy-Balanced Routing Protocol for a Wireless Sensor Network

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lin Li ◽  
Donghui Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Cluster Head ◽  
Low Energy ◽  
Fuzzy Rules ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
Energy Balanced Routing

The wireless sensor network is an intelligent self-organizing network which consists of many sensor nodes deployed in the monitoring area. The greatest challenge of designing a wireless sensor network is to balance the energy consumption and prolong the lifetime of the network, seeing that the nodes can be powered only by batteries in most conditions. An energy-balanced routing protocol (EBRP) for wireless sensor networks is proposed in this paper. In EBRP, we divide the network into several clusters by using K-means++ algorithm and select the cluster head by using the fuzzy logical system (FLS). Since the previous researches did not demonstrate how to get the fuzzy rules for different networks, we propose a genetic algorithm (GA) to obtain the fuzzy rules. We code the rules as a chromosome, and the lifetime of the network is treated as a fit function. Then, through the selection, crossover, and mutation of each generation, the best offspring can be decoded as the best rule for each network model. Through the simulation, comparing with the existing routing protocols such as low-energy adaptive clustering hierarchy (LEACH), low-energy adaptive clustering hierarchy-centralized (LEACH-C), and stable election protocol (SEP), the EBRP prolongs the network lifetime (first node dies) by 57%, 63%, and 63%, respectively.

An Efficient Energy Adaptive Clustering LEACH in Wireless Sensor Network

2010 ◽  
Vol 439-440 ◽  
pp. 510-515
Author(s):  
Lian Xing Zhang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Fault Tolerant ◽  
Wireless Sensor ◽  
Threat Detection ◽  
Critical Systems ◽  
New Paradigm ◽  
Power Sources ◽  
Adaptive Clustering ◽  
Programming Tools

Wireless sensor network (WSN) is an emerging class of systems made possible by cheap hardware, advanced programming tools, complex algorithms, long lasting power sources and energy efficient radio interfaces. Wireless sensor network is a new paradigm in designing fault tolerant mission critical systems, to enable varied applications like threat detection, environmental monitoring, traditional sensing and actuation and much more. The algorithmic approach to WSN differentiates itself from the protocol approach by the fact that the mathematical models used are more abstract, more general, but sometimes less realistic than the models used for protocol design. Experimental results prove that the scheme can get better effect.

scholarly journals Consumption of Energy and Routing Protocols in Wireless Sensor Network

2016 ◽  
Vol 8 (3) ◽  
pp. 76 ◽  
Author(s):  
Ridha Azizi
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocols ◽  
Cluster Head ◽  
Low Energy ◽  
Wireless Sensor ◽  
Simulation Tool ◽  
New Approach ◽  
Adaptive Clustering

Extend the life of a wireless sensor network (WSN) is a fundamental challenge, as they have a limited supply. Multiple protocols and approaches have been proposed to minimize power consumption. Routing protocols and especially the hierarchical approach is one of the techniques used to minimize energy consumption and to improve the duration of network life. In this paper we propose a new approach to transfer and select the CH (Cluster Head). ART-LEACH (Advanced Routing Transfer- Low-Energy Adaptive Clustering Hierarchy) is a self-organizing protocol based on clustering. Our approach is to use energy more evenly the selected nodes as CH. We evaluated the performance of LEACH (Low-Energy Adaptive Clustering Hierarchy) and IB-LEACH (Improved and Balanced Low Energy Adaptive Clustering Hierarchy) protocol with the proposed new approach using MATLAB as a simulation tool. The simulation results showed that our proposal provides a reduction in energy consumption and increase the duration of network life.

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