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Article type: Research Article
Authors: Sebastin Suresh, S.a; * | Prabhu, V.b | Parthasarathy, V.c
Affiliations: [a] Anna University, Chennai, Tamil Nadu, India | [b] Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Tamil Nadu, India | [c] KARPAGAM Academy of Higher Education, Tamil Nadu, India
Correspondence: [*] Corresponding author. S. Sebastin Suresh, Research Scholar, Anna University, Chennai, Tamil Nadu, India. E-mail: [email protected].
Abstract: The Internet of Things (IoT) enabled wireless sensor network (WSN) is now widely employed in various sectors like smart city and vehicle transportation for their expanded capabilities such as data storage, access, and monitoring. The use of smart sensors that continuously collect data from the smart environment makes these possible. Furthermore, these facilitate the easy access of stored data over a secure IoT-gateway for mobile users. This device mobility that allows shifting to multiple locations, makes it challenging to route data across many access points. In this regard, it induces packet loss and improper node selection, which could result in connection failure and network unreliability. This study proposes a new data routing protocol called as Fuzzy Logic Nodes Distributed Clustering for Energy-Efficient Fault Tolerance (F-NDC-EEFT). It can be deployed on any network platform, including mobile and non-mobile nodes. It considers performance metrics such as delivery rate, withstand node aliveness, communication delay, and energy efficiency to find an optimized path for the better performance of IoT enabled WSNs. The clustering approach is applied to the instant data load, which divides it into the distinct node groups. When proposed algorithm is tested alongside existing routing protocols for performance, it is found to save energy, minimize the number of connection failures, boost the throughput, and increase the network’s lifetime.
Keywords: CH eligibility, energy efficiency, fuzzy modules, energy aware routing protocol, IoT enabled WSN
DOI: 10.3233/JIFS-221733
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 5407-5423, 2023
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