Use of Big Data technology in Vehicular Ad-hoc Networks

Big Data technology is becoming ubiquitous and depicting key attention of researchers in almost all areas. VANET is a special form of MANET that uses vehicles as nodes in a network. By applying Big Data technologies to Vehicular Ad-hoc Network (VANET), one can gain useful insight from a huge amount of operational data, to improve traffic management processes such as planning, engineering and operations. VANETs access large data during the real time operations. In this paper we map VANET characteristics to Big Data attributes stated in literature. Further, we evaluate the performance of Dijkstra algorithm used for routing in vehicular networks on Hadoop Map Reduce standalone distributed framework as well as on multinode cluster with 2, 3, 4 and 5 nodes respectively. The results obtained confirm that increasing the number of nodes in Hadoop framework, processing time for the algorithm is greatly reduced.