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Optimizing Ad-Hoc Routing Protocols in WSN to Enhance QoS Parameters Using Evolutionary Computation Algorithms


Affiliations
1 School Of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India
2 Faculty of Medicine, Research Unit of Health Sciences and Technology, University of Oulu, Finland
 

Wireless Sensor Networks (WSNs) have garnered considerable attention within the research community focused on fraternity due to their extensive utilization in healthcare, environmental surveillance, disaster avoidance, farming methods, wildfire detection, and other practical applications. Enormous applications have been developed in the Internet of Things (IoT) era resulting in an ever-increasing number of connected WSN devices. As a result, WSNs consistently face challenges in delivering the required quality of service (QoS) affecting the average end-to-end delay, energy utilization, and packet loss throughout the transmission process. An efficient routing protocol must be designed to address these constraints and improve the operational efficiency of WSNs regarding Quality of Service (QoS) metrics. Motivated by these challenges, this paper presents an advanced routing algorithm by integrating optimization in the AODV routing protocol for ad hoc networks employing Particle Swarm Optimization (PSO). The proposed multipath protocol is termed the EPSO-AODV algorithm. The proposed algorithm is assessed through numerous simulations carried out with varied system setups and parameters. Additionally, the efficiency of the proposed protocol is assessed in comparison to conventional routing protocols including AODV, Dynamic Source Routing (DSR), Destination-Sequenced Distance Vector (DSDV), and Optimized Link State Routing (OLSR) protocols. It is observed from the experimental findings that the proposed approach outperforms existing algorithms and offers several benefits including better energy efficiency, ensuring high packet delivery ratio, throughput, and minimal end-to-end delay delay, reduced normalization load. The proposed protocol efficiently distributes energy usage to enhance throughput and enhance the performance of wireless sensor networks. As per the simulation results, the packet delivery ratio has improved from 81.58% to 91.60% whereas the throughput is observed to be 36.32 kbps for conventional AODV and 74.21 kbps for the proposed algorithm. The routing overhead is lowered by approximately 40% and the AE2E delay was found to be 0.04 lower in comparison to AODV. The residual energy in the context of the EPSO-AODV proposal is less (4981 Joules) than AODV (6344 Joules) which proves the superior efficiency of the proposed algorithm.

Keywords

Ad Hoc On-Demand Distance Vector Routing, Particle Swarm Optimization, Machine Learning, Network Lifespan, Energy Balancing, Localization, Clustering, Routing Overhead, Throughput, End-to-End Delay.
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  • Optimizing Ad-Hoc Routing Protocols in WSN to Enhance QoS Parameters Using Evolutionary Computation Algorithms

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Authors

Rahul Nawkhare
School Of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India
Daljeet Singh
Faculty of Medicine, Research Unit of Health Sciences and Technology, University of Oulu, Finland

Abstract


Wireless Sensor Networks (WSNs) have garnered considerable attention within the research community focused on fraternity due to their extensive utilization in healthcare, environmental surveillance, disaster avoidance, farming methods, wildfire detection, and other practical applications. Enormous applications have been developed in the Internet of Things (IoT) era resulting in an ever-increasing number of connected WSN devices. As a result, WSNs consistently face challenges in delivering the required quality of service (QoS) affecting the average end-to-end delay, energy utilization, and packet loss throughout the transmission process. An efficient routing protocol must be designed to address these constraints and improve the operational efficiency of WSNs regarding Quality of Service (QoS) metrics. Motivated by these challenges, this paper presents an advanced routing algorithm by integrating optimization in the AODV routing protocol for ad hoc networks employing Particle Swarm Optimization (PSO). The proposed multipath protocol is termed the EPSO-AODV algorithm. The proposed algorithm is assessed through numerous simulations carried out with varied system setups and parameters. Additionally, the efficiency of the proposed protocol is assessed in comparison to conventional routing protocols including AODV, Dynamic Source Routing (DSR), Destination-Sequenced Distance Vector (DSDV), and Optimized Link State Routing (OLSR) protocols. It is observed from the experimental findings that the proposed approach outperforms existing algorithms and offers several benefits including better energy efficiency, ensuring high packet delivery ratio, throughput, and minimal end-to-end delay delay, reduced normalization load. The proposed protocol efficiently distributes energy usage to enhance throughput and enhance the performance of wireless sensor networks. As per the simulation results, the packet delivery ratio has improved from 81.58% to 91.60% whereas the throughput is observed to be 36.32 kbps for conventional AODV and 74.21 kbps for the proposed algorithm. The routing overhead is lowered by approximately 40% and the AE2E delay was found to be 0.04 lower in comparison to AODV. The residual energy in the context of the EPSO-AODV proposal is less (4981 Joules) than AODV (6344 Joules) which proves the superior efficiency of the proposed algorithm.

Keywords


Ad Hoc On-Demand Distance Vector Routing, Particle Swarm Optimization, Machine Learning, Network Lifespan, Energy Balancing, Localization, Clustering, Routing Overhead, Throughput, End-to-End Delay.

References





DOI: https://doi.org/10.22247/ijcna%2F2024%2F224448