Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication
Wireless sensor networks (WSNs) have been developed recently to support several applications, including environmental monitoring, traffic control, smart battlefield, home automation, etc. WSNs include numerous sensors that can be dispersed around a specific node to achieve the computing process. In...
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| Format: | Article |
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MDPI AG
2022-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/21/8508 |
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| author | Someah Alangari Marwa Obayya Abdulbaset Gaddah Ayman Yafoz Raed Alsini Omar Alghushairy Ahmed Ashour Abdelwahed Motwakel |
| author_facet | Someah Alangari Marwa Obayya Abdulbaset Gaddah Ayman Yafoz Raed Alsini Omar Alghushairy Ahmed Ashour Abdelwahed Motwakel |
| author_sort | Someah Alangari |
| collection | DOAJ |
| description | Wireless sensor networks (WSNs) have been developed recently to support several applications, including environmental monitoring, traffic control, smart battlefield, home automation, etc. WSNs include numerous sensors that can be dispersed around a specific node to achieve the computing process. In WSNs, routing becomes a very significant task that should be managed prudently. The main purpose of a routing algorithm is to send data between sensor nodes (SNs) and base stations (BS) to accomplish communication. A good routing protocol should be adaptive and scalable to the variations in network topologies. Therefore, a scalable protocol has to execute well when the workload increases or the network grows larger. Many complexities in routing involve security, energy consumption, scalability, connectivity, node deployment, and coverage. This article introduces a wavelet mutation with Aquila optimization-based routing (WMAO-EAR) protocol for wireless communication. The presented WMAO-EAR technique aims to accomplish an energy-aware routing process in WSNs. To do this, the WMAO-EAR technique initially derives the WMAO algorithm for the integration of wavelet mutation with the Aquila optimization (AO) algorithm. A fitness function is derived using distinct constraints, such as delay, energy, distance, and security. By setting a mutation probability P, every individual next to the exploitation and exploration phase process has the probability of mutation using the wavelet mutation process. For demonstrating the enhanced performance of the WMAO-EAR technique, a comprehensive simulation analysis is made. The experimental outcomes establish the betterment of the WMAO-EAR method over other recent approaches. |
| first_indexed | 2024-03-09T18:40:22Z |
| format | Article |
| id | doaj.art-b58614a850ac473a97115c9cde5caf9b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T18:40:22Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b58614a850ac473a97115c9cde5caf9b2023-11-24T06:49:10ZengMDPI AGSensors1424-82202022-11-012221850810.3390/s22218508Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless CommunicationSomeah Alangari0Marwa Obayya1Abdulbaset Gaddah2Ayman Yafoz3Raed Alsini4Omar Alghushairy5Ahmed Ashour6Abdelwahed Motwakel7Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra 11961, Saudi ArabiaDepartment of Biomedical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaDepartment of Computer Sciences, College of Computing and Information System, Umm Al-Qura University, Mecca 24382, Saudi ArabiaDepartment of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Information Systems and Technology, College of Computer Science and Engineering, University of Jeddah, Jeddah 21589, Saudi ArabiaDepartment of Engineering Mathematics and Physics, Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11845, EgyptDepartment of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, Al-Kharj 16278, Saudi ArabiaWireless sensor networks (WSNs) have been developed recently to support several applications, including environmental monitoring, traffic control, smart battlefield, home automation, etc. WSNs include numerous sensors that can be dispersed around a specific node to achieve the computing process. In WSNs, routing becomes a very significant task that should be managed prudently. The main purpose of a routing algorithm is to send data between sensor nodes (SNs) and base stations (BS) to accomplish communication. A good routing protocol should be adaptive and scalable to the variations in network topologies. Therefore, a scalable protocol has to execute well when the workload increases or the network grows larger. Many complexities in routing involve security, energy consumption, scalability, connectivity, node deployment, and coverage. This article introduces a wavelet mutation with Aquila optimization-based routing (WMAO-EAR) protocol for wireless communication. The presented WMAO-EAR technique aims to accomplish an energy-aware routing process in WSNs. To do this, the WMAO-EAR technique initially derives the WMAO algorithm for the integration of wavelet mutation with the Aquila optimization (AO) algorithm. A fitness function is derived using distinct constraints, such as delay, energy, distance, and security. By setting a mutation probability P, every individual next to the exploitation and exploration phase process has the probability of mutation using the wavelet mutation process. For demonstrating the enhanced performance of the WMAO-EAR technique, a comprehensive simulation analysis is made. The experimental outcomes establish the betterment of the WMAO-EAR method over other recent approaches.https://www.mdpi.com/1424-8220/22/21/8508wireless communicationrouting protocolwavelet mutationAquila optimizerwireless sensor networks |
| spellingShingle | Someah Alangari Marwa Obayya Abdulbaset Gaddah Ayman Yafoz Raed Alsini Omar Alghushairy Ahmed Ashour Abdelwahed Motwakel Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication Sensors wireless communication routing protocol wavelet mutation Aquila optimizer wireless sensor networks |
| title | Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication |
| title_full | Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication |
| title_fullStr | Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication |
| title_full_unstemmed | Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication |
| title_short | Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication |
| title_sort | wavelet mutation with aquila optimization based routing protocol for energy aware wireless communication |
| topic | wireless communication routing protocol wavelet mutation Aquila optimizer wireless sensor networks |
| url | https://www.mdpi.com/1424-8220/22/21/8508 |
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