A High Energy Efficiency Approach Based on Fuzzy Clustering Topology for Long Lifetime in Wireless Sensor Networks

Lam, Quynh-Trang; Horng, Mong-Fong; Nguyen, Trong-The; Lin, Jianan; Hsu, Jang-Pong

doi:10.1007/978-3-642-34300-1_35

Cited by 8 publications

(2 citation statements)

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“…The FCM algorithm functions by assigning affiliation to every sensor node corresponding to every cluster center according to the distance between the cluster center and the sensor node. When the sensor nodes are nearestto the cluster center, its memberships in cluster center are the stronger [26,27]. The FCM algorithm is an iterative optimization algorithm that minimizes the following function.…”

Section: Subtractive Clustering Methodsmentioning

confidence: 99%

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Mahboub

En-Naimi

Arioua

et al. 2019

IJECE

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Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period.

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Section: Subtractive Clustering Methodsmentioning

confidence: 99%

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Mahboub

En-Naimi

Arioua

et al. 2019

IJECE

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“…The fuzzy C-means clustering algorithm (FCM), which was developed by Dunn in 1974 and improved by Bezdek in 1987, has been extensively studied and applied [29,30]. FCM is a clustering algorithm that is unsupervised as same as the k-means algorithm with the same cluster division purpose.…”

Section: Fuzzy C-means Clustering Algorithmmentioning

confidence: 99%

Performance evaluation of hierarchical clustering protocols with fuzzy C-means

Barkouk

En-Naimi

Mahboub

2021

IJECE

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The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.

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