Metaheuristic Optimization Based Node Localization and Multihop Routing Scheme with Mobile Sink for Wireless Sensor Networks.

Autor: Soundararajan, S., Kurangi, Chinnarao, Basha, Anwer, Uthayakumar, J., Kalaivani, K., Dhamodaran, M., Shukla, Neeraj Kumar
Předmět:
Zdroj: Wireless Personal Communications; Apr2023, Vol. 129 Issue 4, p2583-2605, 23p
Abstrakt: Wireless Sensor Network (WSN) is composed of independent sensor nodes (SNs) that undergo random deployment in a particular region to sense the atmosphere effectively. The WSNs are applied in real-time applications like medical sector, home automation, traffic monitoring, and ecological observation. Meanwhile the SNs in WSN are energy constrained, routing process is considered as an effective way in achieving energy efficiency and maximize network lifetime. At the same time, node localization (NL) is also a critical challenge in WSN, which aims to analyze the geographical coordinate of unknown nodes through anchor nodes (ACN). Therefore, NL and routing processes are considered NP hard problems and resolved by the use of metaheuristic optimization algorithm. The study proposes a metaheuristic optimization based NL and multihop routing protocol with mobile sink (MONL-MRPMS) for WSN. The proposed MONL-MRPMS technique aims to achieve energy efficacy with accurate NL performance. The MONL-MRPMS technique involves an efficient Coyote Optimization Algorithm (COA) for NL, (COA-NL) in WSNs, assist in determining the location of the nodes iteratively by taking Euclidian distance as fitness into account. Besides, sea gull optimization based Multihop routing (SGO-MHR) protocol is designed for the optimum selection of routes for intercluster transmission. Eventually, a mobile sink (MS) with route adjustment technique is employed for improved energy efficiency of the WSN, which allows adjusting the routes depending upon the movement of MS. A wide-ranging experiments were performed and the obtained results emphasized the supremacy of MONL-MRPMS algorithm over the recent approaches. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index