ew 18(20): e10

Research Article

Smart routing for Vehicle at optimal position with Ant Colony Optimization and AQRV in VANET

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  • @ARTICLE{10.4108/eai.12-9-2018.155566,
        author={J. Prakash and Dr. N. Sengottaiyan and S. Hamsa Nandhini},
        title={Smart routing for Vehicle at optimal position with Ant Colony Optimization and AQRV in VANET},
        journal={EAI Endorsed Transactions on Energy Web and Information Technologies},
        volume={5},
        number={20},
        publisher={EAI},
        journal_a={EW},
        year={2018},
        month={9},
        keywords={Smart route, RSR, Best route, Local QoS Models (LQM) of A Road Segment.},
        doi={10.4108/eai.12-9-2018.155566}
    }
    
  • J. Prakash
    Dr. N. Sengottaiyan
    S. Hamsa Nandhini
    Year: 2018
    Smart routing for Vehicle at optimal position with Ant Colony Optimization and AQRV in VANET
    EW
    EAI
    DOI: 10.4108/eai.12-9-2018.155566
J. Prakash1,*, Dr. N. Sengottaiyan2, S. Hamsa Nandhini3
  • 1: Research Scholar, Department of Computer Science and Engineering, Hindusthan College of Engineering and Technology, Coinbatore Tamilnadu, India – 641032.
  • 2: Supervisor Director Academics Sri Shanmugha College of Engineering and Technology, Sankari Tamilnadu, India – 637304.
  • 3: Assitant Professore Director Academics Kongu Engineering, Erode, Perundurai, Tamil Nadu 638060.
*Contact email: jeevaprakash86@gmail.com

Abstract

The Coimbatore is one of the leading tier two cities in India. Vehicles in this city are increasing day by day. The VANET is a self-organizing network between vehicles. There are so many interesting issues in VANET. So many routing protocols are already availing in the market. In this paper, we put forward an adaptive quality of service (QoS) based smart routing for VANETs with ant colony optimization algorithm find a smart route in Coimbatore city. This smart routing protocol is to adaptively choose the connections in the various available nodes, through which data packets clearance to reach the destination. The selected smart route should fulfill with the QoS constraints and satisfy the best QoS in terms of three metrics, namely connectivity, probability, packet delivery ratio and delay. The AQRV and Ant colony algorithm was simulated. The comparative result was studied at various optimal positions in the city.