An effect of big data technology with ant colony optimization based routing in vehicular ad hoc networks: Towards smart cities

Abstract

Rapid growth in urban population creates various kinds of issues like long hours traffic-jams, pollution which makes the city life insecure and non-liveable. The concept of a smart city is introduced to improve the quality of city life. Smart cities are being developed to satisfy the need for the safety of its users’ and secure journeys over in the urban scenario by proposing the smart mobility concept. At the same time, Vehicular adhoc network (VANET) comes under the type of mobile adhoc network (MANET), wherever the vehicles are treated as nodes in a network. The application of Big Data technologies to VANET gains useful insight from the massive quantity of operational data to enhance traffic management process like planning, engineering as well as operation. During the real-time processes, the VANET generates large data, and the VANET characteristics are mapped to Big Data attributes. Moreover, ant colony optimization (ACO) algorithm is employed for routing in vehicular networks over Hadoop Map Reduce standalone distributed framework and over multi-node cluster with 2, 3, 4 and 5 nodes. The simulation outcomes ensure that the processing time of the algorithm is significant decreases with a rise in the node count of the Hadoop framework.