Abstract:
VANETs help V2V infrastructure communicate efficiently. VANETs have V2V node management, security, and routing issues. Intelligent transportation systems have opened VANET routing, security, and mobility research.
VANET routing optimization for desired traffic scenarios is difficult. Due to vehicle movement, traditional protocols like Adhoc On-demand Distance Vector (AODV), Optimized Link State Routing (OLSR), and Destination Sequence Distance Vector (DSDV) are unsuitable for VANET.
Swarm intelligence routing algorithms like PSO and ACO partially address optimized routing for sparse, dense, and realistic traffic network scenarios in VANET. Most metaheuristics methods have premature convergence, local optima, and slow convergence.
For faster VANET communication, HGFA is suggested. The Firefly algorithm integrates GA features for VANET routing in sparse and dense networks. HGFA outperforms Firefly and PSO techniques in dense and sparse network scenarios by 0.77% and 0.55%, respectively.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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