Hybrid Muddy Soil Fish Optimization-Based Energy Aware Routing in IoT-Assisted Wireless Sensor Networks

Mohammed Rizwanullah (), Hadeel Alsolai, Mohamed K. Nour, Amira Sayed A. Aziz, Mohamed I. Eldesouki and Amgad Atta Abdelmageed
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Mohammed Rizwanullah: Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam Bin Abdulaziz University, AlKharj 16278, Saudi Arabia
Hadeel Alsolai: Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Mohamed K. Nour: Department of Computer Sciences, College of Computing and Information System, Umm Al-Qura University, Mecca 24382, Saudi Arabia
Amira Sayed A. Aziz: Department of Digital Media, Faculty of Computers and Information Technology, Future University in Egypt, New Cairo 11835, Egypt
Mohamed I. Eldesouki: Department of Information System, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, AlKharj 16278, Saudi Arabia
Amgad Atta Abdelmageed: Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam Bin Abdulaziz University, AlKharj 16278, Saudi Arabia

Sustainability, 2023, vol. 15, issue 10, 1-15

Abstract: The seamless operation of interconnected smart devices in wireless sensor networks (WSN) and the Internet of Things (IoT) needs continuously accessible end-to-end routes. However, the sensor node (SN) relies on a limited power source and tends to cause disconnection in multi-hop routes because of a power shortage in the WSN, eventually leading to the inefficiency of the total IoT network. Furthermore, the density of available SNs affects the existence of feasible routes and the level of path multiplicity in the WSN. Thus, an effective routing model is predictable to extend the lifetime of WSN by adaptively choosing the better route for the data transfers between interconnected IoT devices. This study develops a Hybrid Muddy Soil Fish Optimization-based Energy Aware Routing Scheme (HMSFO-EARS) for IoT-assisted WSN. The presented HMSFO-EARS technique majorly focuses on the identification of optimal routes for data transmission in the IoT-assisted WSN. To accomplish this, the presented HMSFO-EARS technique involves the integration of the MSFO algorithm with the Adaptive β -Hill Climbing (ABHC) concept. Moreover, the presented HMSFO-EARS technique derives a fitness function for maximizing the lifespan and minimizing energy consumption. To demonstrate the enhanced performance of the HMSFO-EARS technique, a series of experiments was performed. The simulation results indicate the better performance of the HMSFO-EARS algorithm over other recent approaches with reduced energy consumption, less delay, high throughput, and extended network lifetime.

Keywords: IoT; routing; metaheuristics; muddy soil fish optimization; fitness function (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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