5200 IEEE TRANSACTIONS ONVEHICULAR TECHNOLOGY, VOL. 58, NO. 9, NOVEMBER 2009 Small-Scale and Large-Scale Routing in Vehicular Ad Hoc Networks Wenjing Wang, Member, IEEE, Fei Xie, Member, IEEE, and Mainak Chatterjee Abstract—A vehicular ad hoc network (VANET) is a highly mobile wireless ad hoc network that is targeted to support ve- hicular safety, traffic monitoring, and other applications. Mobility models used in traditional mobile ad hoc networks cannot directly be applied to VANETs since real-world factors such as road layouts and traffic regulations are not considered. In this paper, we propose a vehicular mobility model that reflects real-world vehicle movement and study the performance of packet-routing protocols. First, we study the routing in small-scale VANETs and propose two routing schemes: 1) connection-based restricted forwarding (CBRF) and 2) connectionless geographic forwarding (CLGF). With the insights obtained, we consider routing in large-scale VANETs. Since road complexity and traffic variety may cause many potential problems that existing routing protocols cannot address, we introduce a two-phase routing protocol (TOPO) that incorporates road map information. The proposed protocol defines an overlay graph with roads of high vehicular density and access graphs that are connected to the overlay. While in the overlay, packets are forwarded along a precalculated path. As far as access routing is concerned, we employ the aforementioned CBRF and CLGF schemes and send packets to the overlay or handle packets delivered from the overlay. We argue that the TOPO can serve as a framework that integrates existing VANET routing protocols. We also consider data diversity in VANETs and design the TOPO as an intelligent transportation system (ITS)-friendly protocol. To validate our design philosophy and the routing protocol, we use different areas in the city of Orlando, FL, and generate vehicular mobility traces, following our mobility models. We feed the traces to network simulators and study the routing behavior. Simulation results demonstrate the performance and effectiveness of the pro- posed routing protocols for large-scale VANET scenarios. Index Terms—Mobility, networks, routing, vehicular ad hoc network (VANET). I. I NTRODUCTION T HE approval of the 75-MHz spectrum at 5.9 GHz for dedicated short-range communications (DSRC) [9] by the Federal Communications Commission and the successful deployments of WLAN technologies are making vehicular ad hoc networks (VANETs) a reality [5], [27], [36]. In recent years, the VANET has emerged as a research area that has received increased attention from the research community. However, due to the cost and difficulty associated with the implementation Manuscript received September 22, 2008; revised February 23, 2009 and April 23, 2009. First published June 19, 2009; current version pub- lished November 11, 2009. The review of this paper was coordinated by Prof. H. Hassanein. The authors are with the School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816 USA (e-mail: wenjing@eecs.ucf.edu; xiefei@eecs.ucf.edu; mainak@eecs.ucf.edu). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TVT.2009.2025652 of VANETs in the real world, computer simulations remain as one of the primary techniques in investigating networking characteristics of VANETs. In this regard, it is very important to adopt realistic vehicular mobility models and design network protocols that are capable of delivering good end-to-end perfor- mance in such highly mobile environments. It is widely accepted that the underlying mobility models greatly affect ad hoc network performance [3], [6], [41]. Many studies on mobile ad hoc networks (MANETs) have used random waypoint (RWP) or the Manhattan model to simulate node movements in an open field. Although such mobility models work well in certain scenarios, they are not suitable for VANETs, simply because the movement of vehicles is constrained by the layouts of the roads. Moreover, traffic regu- lations (e.g., speed limits and traffic lights) and driver behaviors (e.g., overtaking or following) make realistic vehicular mobility far different from the commonly used ones in MANETs. The traffic simulator framework introduced by Saha and Johnson [31] makes it convenient to use the real map of the U.S. in the form of a graph model where the edges represent the roads and the vertices represent the intersections. The (map) input to the simulator is the data provided by the U.S. Census Bureaus’ Topologically Integrated Geographic Encoding and Referencing system (TIGER) Project [34]. In their framework, each vehicle randomly chooses a source and a destination on the map and moves along the route, which is calculated using Dijkstra’s single-source shortest path algorithm. The output of the framework is the trace of the vehicles on the map, the data format of which is compatible with the network simulator ns-2 [45]. However, the framework only uses simple mobility models (similar to RWP [21]) and does not include realistic vehicle mobility models. Using the aforementioned simulator framework, it is possible to design a traffic simulator with a sound mobility model, which generates realistic vehicle mobility traces that can be used for network simulation. 1 Moreover, we are motivated to investigate the performance of existing routing protocols in VANETs and design new protocols. We study the routing problem in both small (e.g., less than 1 mi 2 ) and large areas (e.g., tens of the mile scale). In small-area routing, we pro- pose and compare two routing schemes: 1) connection-based restricted forwarding (CBRF) and 2) connectionless geographic forwarding (CLGF). Considering different road topologies, we conduct extensive simulations to evaluate the performance of the proposed protocols, as well as other existing counterparts, 1 We make the traces compatible with both ns-2 and GTNetS [10]. 0018-9545/$26.00 © 2009 IEEE Authorized licensed use limited to: SUNY Buffalo. Downloaded on June 04,2010 at 14:52:53 UTC from IEEE Xplore. Restrictions apply.