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AIMS Mathematics
Article . 2023 . Peer-reviewed
Data sources: Crossref
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AIMS Mathematics
Article . 2023
Data sources: DOAJ
https://dx.doi.org/10.60692/d7...
Other literature type . 2023
Data sources: Datacite
https://dx.doi.org/10.60692/z1...
Other literature type . 2023
Data sources: Datacite
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A fuzzy logic and DEEC protocol-based clustering routing method for wireless sensor networks

منطق غامض وطريقة توجيه تجميع قائمة على بروتوكول DEEC لشبكات الاستشعار اللاسلكية
Authors: orcid S. Neelakandan;
S. Neelakandan
ORCID
Harvested from ORCID Public Data File

S. Neelakandan in OpenAIRE
orcid Abbas Mardani;
Abbas Mardani
ORCID
Harvested from ORCID Public Data File

Abbas Mardani in OpenAIRE
orcid bw Prakash Mani;
Prakash Mani
ORCID
Derived by OpenAIRE algorithms or harvested from 3rd party repositories

Prakash Mani in OpenAIRE
orcid bw Arunodaya Raj Mishra;
Arunodaya Raj Mishra
ORCID
Derived by OpenAIRE algorithms or harvested from 3rd party repositories

Arunodaya Raj Mishra in OpenAIRE
P Ezhumalai;

A fuzzy logic and DEEC protocol-based clustering routing method for wireless sensor networks

Abstract

<abstract> <p>Power-efficient wireless sensor network routing techniques (WSN). Clustering is used to extend WSNs' lifetimes. One node act as the cluster head (CH) to represent the others in communications. The member nodes are less important than the cluster hub (CH) in the clustering procedure. Fuzzy techniques based on clustering theory may provide evenly distributed loads. In this study, we provide a fuzzy-logic-based solution that factors in distance to base station (BS), number of nodes, remaining energy, compactness, distance to communicate within a cluster, number of CH, and remaining energy. Fuzzy clustering has a preliminary and final step. First, we select CH based on distance to the base station (BS), remaining node vigor, and node compactness. In the second phase, clusters are created by combining nodes that aren't already in a CH, using density, outstanding vigor, and detachment as limitations. The proposed solution increases load balancing and node longevity. This work provides a unique hybrid routing technique for forming clusters and managing data transfer to the base station. Simulation findings confirm the protocol's functionality and competence. Reduced energy use keeps network sensor nodes online longer. The framework outperforms Stable Election Protocol (SEP), hybrid energy-efficient distributed clustering (HEED), and Low Energy Adaptive Clustering Hierarchy (LEACH). Using the nodes' energy levels to create a grid pattern for the clusters gave four clusters. In addition, the proposed method has a 4347%, 41.46%, 39.26%, 37.57% and 35.67% reduction in average energy consumption when compared with the conventional algorithms. The proposed technologies could increase the network's lifetime, stability interval, packet transfer rate (throughput), and average energy. The suggested protocol is at least 50% better in every statistic that was looked at, such as network lifetime, stability interval, packet transmission rate (throughput), and average energy use.</p> </abstract>

Keywords

Wireless Home Automation Systems, Artificial intelligence, Computer Networks and Communications, Mobile Sensor Deployment, Structural engineering, Node (physics), Clustering Algorithms, Engineering, Cluster analysis, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Base station, Efficient energy use, Electrical and Electronic Engineering, wireless sensor networks, energy efficiency, network lifetime, Computer network, Routing (electronic design automation), Wireless Sensor Networks: Survey and Applications, deec, Routing Techniques, Secure Routing, Computer science, Distributed computing, Routing protocol, Fuzzy logic, Energy consumption, routing, Electrical engineering, Computer Science, Physical Sciences, fuzzy logic, Security in Wireless Sensor Networks, Wireless Sensor Networks, Mathematics, Wireless sensor network, clustering

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