International Journal of Computer Networks and Applications

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Dynamic Integration of Fast Furious Cheetah Optimization for Efficient and Secure Routing in Vehicular Ad Hoc Networks


Affiliations
1 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
 

This research addresses the intertwined challenges of routing efficiency and data security in Vehicular Ad Hoc Networks (VANETs), characterized by dynamic Vehicle-to- Vehicle (V2V) communication. To bolster the Ad Hoc On- Demand Distance Vector (AODV) protocol, Route Life Time Enhanced AODV (RLE-AODV) is introduced, integrating Fast Furious Cheetah Optimization (FFCO) at each protocol step for comprehensive optimization. The robust security measures are concurrently incorporated using an enhanced iteration of Elliptic Curve Cryptography (ECC), which is seamlessly integrated into the secure routing framework. The study meticulously explores the synergistic integration of FFCO with RLE-AODV and ECC, optimizing routing efficiency while fortifying data security. After integration with ECC, the framework transforms into Fast Furious Cheetah Optimization- Based Secured Routing (FFCOSR), ensuring the integrity and confidentiality of data exchanged between vehicles. Through extensive simulations, the FFCOSR framework demonstrates superior performance and heightened security compared to conventional approaches in V2V VANETs. By orchestrating FFCO within RLE-AODV, the approach dynamically adjusts routing parameters to adapt to changing network conditions, prolonging route stability and enhancing overall network performance. This research significantly advances state-of-theart efficient and secure vehicular communication, offering valuable insights into the synergy of optimization techniques for addressing multifaceted network challenges. The proposed FFCOSR framework represents a promising avenue for improving the reliability and security of V2V communication in VANETs, with potential applications in real-world scenarios where robustness and efficiency are paramount.

Keywords

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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  • Dynamic Integration of Fast Furious Cheetah Optimization for Efficient and Secure Routing in Vehicular Ad Hoc Networks

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Authors

A. Sheela Rini
Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
C. Meena
Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India

Abstract


This research addresses the intertwined challenges of routing efficiency and data security in Vehicular Ad Hoc Networks (VANETs), characterized by dynamic Vehicle-to- Vehicle (V2V) communication. To bolster the Ad Hoc On- Demand Distance Vector (AODV) protocol, Route Life Time Enhanced AODV (RLE-AODV) is introduced, integrating Fast Furious Cheetah Optimization (FFCO) at each protocol step for comprehensive optimization. The robust security measures are concurrently incorporated using an enhanced iteration of Elliptic Curve Cryptography (ECC), which is seamlessly integrated into the secure routing framework. The study meticulously explores the synergistic integration of FFCO with RLE-AODV and ECC, optimizing routing efficiency while fortifying data security. After integration with ECC, the framework transforms into Fast Furious Cheetah Optimization- Based Secured Routing (FFCOSR), ensuring the integrity and confidentiality of data exchanged between vehicles. Through extensive simulations, the FFCOSR framework demonstrates superior performance and heightened security compared to conventional approaches in V2V VANETs. By orchestrating FFCO within RLE-AODV, the approach dynamically adjusts routing parameters to adapt to changing network conditions, prolonging route stability and enhancing overall network performance. This research significantly advances state-of-theart efficient and secure vehicular communication, offering valuable insights into the synergy of optimization techniques for addressing multifaceted network challenges. The proposed FFCOSR framework represents a promising avenue for improving the reliability and security of V2V communication in VANETs, with potential applications in real-world scenarios where robustness and efficiency are paramount.

Keywords


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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DOI: https://doi.org/10.22247/ijcna%2F2024%2F224449