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• W2912943906 abstract "In wireless sensor networks, the energy source is limited to the capacity of the sensor node's battery. Clustering in WSN can help with reducing energy consumption because transmission energy is related to the distance between sender and receiver. In this paper, we propose a fuzzy logic model for cluster head election. The proposed model uses five descriptors to determine the opportunity for each node to become a CH. These descriptors are: residual energy, location suitability, density, compacting, and distance from the base station. We use this fuzzy logic model in proposing the Fuzzy Logic-based Energy-Efficient Clustering for WSN based on minimum separation Distance enforcement between CHs (FL-EEC/D). Furthermore, we adopt the Gini index to measure the clustering algorithms' energy efficiency in terms of their ability to balance the distribution of energy through WSN sensor nodes. We compare the proposed technique FL-EEC/D with a fuzzy logic-based CH election approach, a k-means based clustering technique, and LEACH. Simulation results show enhancements in energy efficiency in terms of network lifetime and energy consumption balancing between sensor nodes for different network sizes and topologies. Results show an average improvement in terms of first node dead and half nodes dead." @default.
• W2912943906 created "2019-02-21" @default.
• W2912943906 creator A5007298060 @default.
• W2912943906 creator A5014712692 @default.
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• W2912943906 date "2019-01-29" @default.
• W2912943906 modified "2023-10-01" @default.
• W2912943906 title "Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks" @default.
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• W2912943906 doi "https://doi.org/10.3390/s19030561" @default.
• W2912943906 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6387035" @default.
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