Fuzzified Swarm Intelligence Framework Using Fpsor Algorithm for High-Speed Manet

Gopalan, Harihara

doi:10.21203/rs.3.rs-288901/v1

Cited by 1 publication

(1 citation statement)

References 6 publications

(6 reference statements)

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“…A fuzzified Particle Swarm Optimization oriented Routing (FPSOR) algorithm is proposed, (10) aiming to minimize data loss and maximize MANET lifetime by optimizing energy-efficient routes. By integrating fuzzification techniques with Particle Swarm Optimization, FPSOR selects paths with lower energy consumption, evaluated through fitness values, enhancing overall routing efficiency in IoT-enabled MANETs.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhanced Whale Optimization Algorithm for Multi-Objective Node Disjoint Routing

Hussain,

Sugumar

2024

IJST

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Objectives: The research goal is to identify node-disjoint pathways maximizing path lifetime, delivery ratio, etc. while establishing several node-disjoint paths to optimize routing and enhance interference reduction and PDR efficiency. Methods: In the MANET, the Enhanced Whale Optimization Algorithm (EWOA) is utilized to discover the most secure routing path. The dataset used in this research comprises simulated scenarios representing various network conditions and configurations, allowing for a comprehensive evaluation of the proposed work. The software employed for simulation and analysis includes an NS-3 network simulation tool, allowing the model to evaluate the performance of the proposed routing protocol in diverse MANET scenarios. The parameters considered during the evaluation include throughput, end-to-end delay, packet delivery ratio (PDR), and routing overhead. The modifications involve enhancing the routing algorithm to prioritize node-disjoint pathways, thus improving interference reduction, energy efficiency, and overall network performance. Findings: The EWOA for Multi-Objective Node Disjoint Routing demonstrates superior performance compared to existing routing protocols such as SRABC and OLSR across various key metrics. Specifically, in terms of end-to-end delay, EWOA consistently outperforms SRABC and OLSR by reducing delay by 1.3% and 4.7%, respectively. Additionally, EWOA achieves a higher packet delivery ratio, surpassing SRABC and OLSR by 4.3% and 0.4%, respectively. Moreover, EWOA exhibits higher throughput, with a throughput increase of 11.3% compared to SRABC and 6.2% compared to OLSR. Furthermore, EWOA demonstrates lower routing overhead, reducing overhead by 9.6% compared to SRABC and 3.1% compared to OLSR. These findings highlight the efficacy of EWOA in optimizing multi-objective routing in MANETs, offering improved network performance and efficiency compared to existing protocols. Novelty: The Multi-Objective Node Disjoint Routing Protocol with Enhanced Whale Optimization is utilized in MANET to choose the best route, reducing latency resulting from link failure and distributing traffic loads across multiple paths. Keywords: Optimization, Whale Optimization Algorithm (WOA), Optimized Link State Routing (OLSR), Secure Routing Algorithm Blockchain Technology (SRABC)), MANET

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Section: Literature Reviewmentioning

confidence: 99%