Multiple Relay Nodes Selection Scheme using Exit Time Variation for Efficient Data Dissemination in VANET

Abstract

Efficient Data dissemination in VANET is still the challenge because of variable speed of vehicles, road conditions, frequent fragmentation etc. In this article a selective forwarding data dissemination scheme using exit time differences in vehicles for highway lanes scenario is proposed that focuses on the solution of broadcast storm, less coverage, transmission delay and reliable data delivery. Our approach is selecting multiple forwarding nodes to increase coverage in less delay. In this article road lanes concept is used to identify the moving node direction. Redundant regions and zones technique in proposed approach is reducing the processing of parameters at significant extents. Simulation of proposed approach is done using NS2 and SUMO. Output of implementation is compared with unidirectional flooding, KB_Selective, and LT_Selective techniques. Result analysis shown that the proposed technique is much efficient and it increases the rate of coverage up to 23%. Also it reduces the delay up to 18% in data delivery ratio. This methodology also improves the performance of system by increasing the throughput and reducing the collision rate in comparison with other methods.

A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning

“…These networks play an important role in transforming road safety, optimizing traffic flow, and enhancing the passenger experience [1][2][3]. However, data dissemination in VANETs involves challenges related to optimizing the dissemination process, ensuring reliable data delivery, minimizing latency, and utilizing available resources efficiently [4]. These aspects often involve searching for optimal routes, managing communication overhead, dealing with intermittent connectivity, and ensuring the dissemination of information among vehicles in a timely and efficient manner [5,6].…”