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Optimization of Performance Parameter for Vehicular Ad-hoc NETwork (VANET) Using Swarm Intelligence

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Abstract

Vehicular Ad-hoc NETwork (VANET) is a subcategory of Mobile Ad-hoc NETwork (MANET) which is one of the popular emerging research areas. On one side increase in the number of vehicles, and on the other side due to the presence of communication unit i.e. On Board Unit (OBU) in vehicles helped in the creation of a new network called as VANET. VANET is becoming so popular that it is widely used for different applications that may be safety or non-safety applications. An effective routing protocol is required for the efficient use of VANET for different applications which can optimize different generic parameters of VANET like end-to-end delay, number of hops, etc. Altough multiple paths exist between a source and a destination but the routing protocols evaluate a single path for the transmission of information packets based on parameters like shortest distance towards the destination, density of vehicles, number of hops, etc. Different swarm intelligence techniques like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), etc. can be used in VANET to optimize the parameters used in the routing protocol. In this chapter, Ant Colony Optimization (ACO) is used to establish multiple routes between nodes which is vital in the network where network connectivity is random and is frequently changing. This also helps in the parallel transmission of packets in multi-path which reduces end-to-end delay. For this proposed work, a variation of end-to-end delay with respect to transmission distance and a number of vehicles is compared with the existing VANET routing protocol i.e. Geographic Source Routing (GSR), Anchor based Street Traffic Aware Routing (A-STAR). The comparison shows that the proposed work performs better as compared to GSR and A-STAR. To implement multi-path routes MongoDB—an open source distributed database is used and the corresponding operation on the database is implemented using node-red. Selection of effective route and intermediate hop for the transmission of emergency information is essential. The optimized route in VANET not only saves the overall transmission time but also reduces the end-to-end delay. For the optimization of route and number of hops in VANET, another swarm intelligence technique i.e. Particle Swarm Intelligence (PSO) can be used through which the transmission of emergency information with optimum delay is proposed.

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Correspondence to Biswa Ranjan Senapati .

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Ranjan Senapati, B., Mohan Khilar, P. (2020). Optimization of Performance Parameter for Vehicular Ad-hoc NETwork (VANET) Using Swarm Intelligence. In: Rout, M., Rout, J., Das, H. (eds) Nature Inspired Computing for Data Science. Studies in Computational Intelligence, vol 871. Springer, Cham. https://doi.org/10.1007/978-3-030-33820-6_4

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