Swarm Intelligence based Efficient Routing Algorithm for Platooning in VANET through Ant Colony Optimization
Gagan Deep Singh1, Manish Prateek2, Hanumat Sastry G3

1Gagan Deep Singh, School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India.
2Dr. Manish Prateek, School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India.
3Dr. Hanumat Sastry G, School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1238-1244 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7888078919/19©BEIESP | DOI: 10.35940/ijitee.I7888.078919
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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: Today’s era is of smart technology, Computing intelligence and simulations. Many areas are now fully depended on simulation results for implementing real time workflow. Worldwide researchers and many automobile consortium are working to make intelligent Vehicular Ad hoc Network but till yet it is just a theory-based permutation. If we take VANET routing procedures then it is mainly focusing on AODV, DSDV and DSR routing protocols. Similarly, one more area of Swarm Intelligence is also attained attention of industry and researchers. Due the behavior of dynamic movement of vehicle and ants, Ant Colony Optimization is best suited for VANET performance simulations. Much of the work has already done and in progress for routing protocols in VANET but not focused on platooning techniques of vehicle nodes in VANET. In our research idea, we came up with a hypothesis that proposes efficient routing algorithm that made platooning in VANET optimized by minimizing the average delay waiting and stoppage time. In our methodology, we have used OMNET++, SUMO, Veins and Traci for testing of our hypothesis. Parameters that we took into consideration are end-to-end delay as an average, packet data delivery ratio, throughput, data packet size, number of vehicle nodes etc. Swarm Intelligence has proved a way forward in VANET scenarios and simulation for more accurate results. In this paper, we implemented Ant Colony Optimization technique in VANET simulation and proved through results that if it integrates with VANET routing scenarios then result will be at its best.
Keywords: Swarm Intelligence, Simulation, VANET, Platooning, Ant Colony Optimization.

Scope of the Article: Swarm Intelligence