Security and Connectivity Analysis in Vehicular Communication Networks

Introduction

Next generation intelligent transport systems (NGITSs) enable vehicles to communicate with its neighbors through vehicular ad-hoc networks (VANETs) connectivity and exchange information with road-side units (RSUs) as well as road communication gateways (RCGs), installed along the roads, through vehicle-to-road (V2R) or vehicle-to-infrastructure (V2I) connectivity (Alshaer & Elmirghani, 2009; Alshae & Horlait, 2004; Alshaer & Horlait, 2005). Communication-enabled vehicles (CEVs) are equipped with small-sized wireless devices with increasing computing capabilities which can enable them to network together through peer-to-peer (P2P) communications without the need for fixed communication infrastructure (Blum & Eskandarian & Hoffman, 2004; Hartenstein & Laberteaux, 2008). Reliable VANETs require establishing security and privacy techniques to secure vehicular information messages delivery. VANET security should (i) ensure the information received by vehicle nodes is correct and (ii) verify message integrity and source authentication (Sun & Zhang & Zhang & Fang, 2010). Because of the high and fluctuating mobility of vehicle nodes and transmission power constraints, a VANET might suffer continuous and persistent disruptions. This makes it challenging to maintain security and connectivity of VANET at a determined level.

VANET connectivity ensures the relay of information messages from a vehicle to reach all the other vehicles in the network. To guarantee this connectivity, a road must be sufficiently dense. If the vehicles are too sparsely distributed, the distance between two consecutive vehicles may exceed their radio transmission range, which makes them unable to communicate, causing disconnections in the network connecting them. The number of vehicle nodes involved in VANETs may vary, depending on the change in the transmission ranges assigned to vehicle nodes. A vehicle node that transmits at a large transmission range will increase the probability of finding a receiver in the desired direction and significantly contribute in the successful data transmission range. But, this may result in a higher probability of collisions with other data transmissions and increase energy (power) consumption. The converse is correct for short transmission range.

Despite vehicles in VANETs are highly mobile, both velocity and flow of vehicles are dependent on vehicle density (Nagatani, 2002). The increase in vehicle density causes traffic to shift from free-flow stage, where vehicles movement is unrestricted, to traffic jams caused by dense traffic. While many research studies have been conducted on the connectivity of VANETs (Panichpapiboon & Atikom, 2008; Santi & Blough, 2003; Penrose,1999; Desai & Manjunath, 2002; Panichpapiboon & Pattara-atikom, 2008), most of them rely on the crucial assumption that the inter-vehicle spacing between consecutive vehicles is exponentially distributed. Although an exponential distribution is a good approximation for the inter-vehicle spacing in extremely light traffic conditions, a new empirical analysis (Cheng & Panichpapiboon, 2012) suggests that in a moderate condition the inter-vehicle spacing better be described by other statistical distributions. If the inter-vehicle spacing distribution is not exponential, how does it affect the connectivity analysis? To what extent would the density and the transmission range required for network connectivity change if the inter-vehicle spacing distribution was not exponential? This chapter answers these questions and associates connectivity analysis with security.