Provide a Way to Improve the AODV Algorithm for Routing Vehicle Adhoc Networks (VANETs) by Using Modified Shuffled Frog Leaping Algorithm

One of the most important challenges of inter-vehicle networks is the rapid mobility of
nodes (vehicles) and their displacement that changes the network topology and,
consequently, greatly reduces its scalability. In these networks for each packet to the lack
of communication infrastructure, routing is done independently. and road and traffic
signs and obstacles on the lane and lanes, and information about the distance and speed
of other vehicles are displayed instantly, which helps drivers make decisions to ensure
safety and prevent accidents and traffic jams.Therefore, our aim in this paper is to
provide a solution to drastically reduce time in selecting the optimal path and increase
network scalability using the modified Frog Jump algorithm due to the use of the best
local displacements and based on the best, efficient random search implementation and
with high speed. Is convergence. Finally, we evaluated normalized routing load, packet
delivery rate, and average end-to-end latency criteria. The simulation results show that
the proposed algorithm is recorded for the criteria of average packet delivery rate equal to
100%, normalized routing load equal to 19% and mean end-to-end latency of 9.9
compared to locust algorithms. Particle swarm and genetics work better.