Abstract:
VANET data dissemination must be done carefully to avoid congestion and broadcast storms. Multi-metric approaches’ implicit conflicting nature requires multi-objective optimization algorithms. Meta-heuristics with high solution interactions can optimize.
Meta-heuristic search algorithm firefly was chosen. Objective decomposition, archive management, and controlled mutation for exploration and exploitation balance were added to firefly optimization to find more dominant solutions.
AJ-MOFA stands for adaptive jumping multi-objective firefly algorithm. After that, CFM was integrated with AJ-MOFA. It has three main parts. Clustering uses arbitration based on the cluster head score, forwarding uses probabilistic forwarding, and AJ-MOFA uses AJ-MOFA.
CFM’s solution space design used two variables: forwarding probability and cluster maximum nodes. PDR, E2E-delay, and dropped packets are used in multi-objective optimizations.
AJ-MOFA and CFM outperform benchmarks in multi-objective optimization and networking metrics, making them promising VANET data dissemination algorithms. The results showed a 60% PDR, 6.6-second E2E delay, and almost nine dropped packets over the course of the experiment, which was comparable to the benchmarks.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
Did you like this final year project?
To download this project Code with thesis report and project training... Click Here
