On the Use of Data Mining Techniques in Vehicular Ad Hoc Network

Abstract

As vehicles become more intelligent, it is predictable that in the near future they will be outfitted with a wireless comparison. This will allow the construction of vehicular networks, commonly referred to as VANETs, as an example of mobile ad hoc networks where cars are the mobile nodes. VANETs (Vehicular Ad hoc Networks) are vastly mobile wireless ad hoc networks and will cooperate an imperative role in public safety communications and commercial applications. Mobilization of these VANETs aim of the mission and duties for the rapid changes in topology and dynamics of high-speed car. Position based routing protocols are becoming trendy due to development and accessibility of GPS devices. One of the major VANETs question often leads to rupture of the corridor high-speed vehicle dynamics, which leads to a broken step, which leads to low throughput and high overhead costs. VANET has become a dynamic spot of research in the last years; one of the important and promising research topics is applying data mining techniques to extract useful patterns from VANET, such as clustering, association, classification, and more. Therefore this paper surveys some of VANET applications that used data mining techniques.