Adaptive Connectivity Aware Routing Protocol for Wireless Vehicular Networks

Abstract

Multi-hop vehicle-to-vehicle communication is useful for supporting many vehicular applications that provide drivers with safety and convenience. Developing multi-hop communication in vehicular ad hoc networks (VANETs) is a challenging problem due to the rapidly changing topology and frequent network disconnections, which cause failure or inefficiency in traditional ad hoc routing protocols. We propose an adaptive connectivity aware routing (ACAR) protocol that addresses these problems by adaptively selecting an optimal route with the best network connectivity-quality (CQ) based on statistical and real-time density data that are gathered through an on-the-fly density collection process. The CQ metric models the joint probability that a network is connected and a packet is successfully delivered in this network. The protocol consists of two parts: 1) select an optimal route, consisting of road segments, with the best CQ, and 2) in each road segment of the chosen route, select the most efficient multi-hop path that will improve the delivery ratio and throughput. The optimal route is selected using our connectivity-quality metric that takes into account vehicles densities and traffic light periods to estimate the probability of network connectivity and data delivery ratio for transmitting packets. Our simulation results show that the proposed ACAR protocol outperforms existing VANETs routing protocols, e.g. the delivery ratio of ACAR is 19% higher than VADD, the second best protocol.

ACAR is built upon geographic routing which requires every vehicle to broadcast its location information to its neighbors, and this process will compromise user's location privacy. To address this issue, we proposed a dummy-based location privacy protection (DBLPP) protocol in VANETs. In DBLPP, routing decision is made based upon the dummy distance to destination (DOD), instead of user's true location. In this scheme, a user's true location and identification information are preserved, so the user's location privacy is protected. Simulation results show that the DBLPP provides similar network performances as other routing protocols, and achieves a higher level of location privacy protection on vehicles in networks. This location privacy protection scheme can be easily added to other geographic routing protocols.