Data Dissemination Scheme for VANET using Genetic algorithm and Particle Swarm Optimization
Tahera Mahmood1, Tulika2

1Tahera Mahmood*, Department of Computer Science SHUATS, Prayagraj, (U.P.) India.
2Dr. Tulika, Assistant Professor, Department of Computer Science and Information Technology, Sam Higginbottom Institute of Agriculture Technology and Sciences, Allahabad (U.P), India.

Manuscript received on May 21, 2021. | Revised Manuscript received on May 31, 2021. | Manuscript published on May 30, 2021. | PP: 322-328 | Volume-10 Issue-1, May 2021. | Retrieval Number: 100.1/ijrte.A59700510121 | DOI: 10.35940/ijrte.A5970.0510121
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: A vehicular ad hoc network (VANET) consist of moving vehicles connected via wireless technology e.g., Wireless Access in Vehicular Environment (WAVE) for the aim of exchanging information. Therefore data dissemination in VANET has become issue of debate for researcher. In VANET broadcasting play an important role. The aim of VANET is to ensure passenger safety through emergency message. With multiple objectives broadcast storm is assumed to be an NP-Hard problem. In this paper we propose DDV algorithm to solve broadcast storm problem. Fitness function has used to optimize the objective of proposed algorithm. The proposed algorithm producing better optimization results. We are considering a highway scenario in city with dynamic rotation, to evaluate the performance of the DDV algorithm we compare the result with Smart flooding techniques, MOGA (Multi Objective Genetic algorithm) [1] and EEADP. Our result show the better performance in terms of reduce the number of retransmission, increase the packet delivery ratio and provide better throughput. 
Keywords: VANET, Broadcasting, Genetic Algorithm GA, Partial Swarm Optimization (PSO), Geographical Area, Rate of Evaluation, Smart flooding, MOGA.