The integration of VANETs with Internet is required if vehicles are to access IP-based applications. A vehicle must have an IP address, and the IP mobility service should be supported during the movement of the vehicle. VANET standards such as WAVE or C-ITS use IPv6 address auto configuration to allocate an IP address to a vehicle. In C-ITS, NEMO-BS is used to support IP mobility. The vehicle moves rapidly, so reallocation of IP address as well as binding update occurs frequently. The vehicle' communication, however, may be disrupted for a considerable amount of time, and the packet loss occurs during these events. Also, the finding of the home address of the peer vehicle is not a trivial matter. We propose a network based identifier locator separation scheme for VANETs. The scheme uses a vehicle identity based address generation scheme. It eliminates the frequent address reallocation and simplifies the finding of the peer vehicle IP address. In the scheme, a network entity tracks the vehicles in its coverage and the vehicles share the IP address of the network entity for their locators. The network entity manages the mapping between the vehicle's identifier and its IP address. The scheme excludes the vehicles from the mobility procedure, so a vehicle needs only the standard IPv6 protocol stack, and mobility signaling does not occur on the wireless link. The scheme also supports seamlessness, so packet loss is mitigated. The results of a simulation show that the vehicles experience seamless packet delivery.

The potential of infrastructureless vehicular ad hoc networks (VANETs) for providing multihop applications is quite significant. Although the Epidemic Routing protocol performs well in highly mobile and frequently disconnected VANETs with low vehicle densities or light packet traffic loads, its performance degrades greatly in environments of high vehicle density together with heavy packet traffic loads that create serious bandwidth contention and frequent collisions. We propose a new epidemic routing protocol in urban environments called Greedy Zone Epidemic Routing (GZER), in which the neighbors of a vehicle are divided into different zones according to their physical locations. Each vehicle maintains a summary vector (SV) of packets buffered locally and zone summary vectors (ZSVs) of all packets buffered in each zone. Whether the infection will be transmitted in each zone is decided by the difference between SV and ZSV. Simulation results show that the proposed GZER protocol outperforms the existing solutions significantly, especially in the environments of high vehicle densities together with heavy packet traffic loads.

Video streaming uploading over vehicular ad hoc networks (VANETs) can support many interesting applications. Due to the high mobility and dynamic topology of VANETs, how to support video streaming using wireless communications between vehicles and road-side access points still remains an open issue. In this paper, we propose a geographical uploading scheme, called MPVUS, which uses the moving prediction to keep the stable forwarding and reduce the high link failure probability over VANETs. The scheme also decides the AP switch opportunity by traffic flow estimation, so as to adjust the forwarding direction timely to avoid the short-sighted switch decision. Simulation results demonstrate the effectiveness of our scheme, which can achieve good performance in terms of the start-up delay, playback interruption ratio and video frame distortion.

The past decade has witnessed a growing interest in vehicular networking. Initially motivated by traffic safety, vehicles equipped with computing, communication and sensing capabilities will be organized into ubiquitous and pervasive networks with a significant Internet presence while on the move. Large amount of data can be generated, collected, and processed on the vehicular networks. Big data on vehicular networks include useful and sensitive information which could be exploited by malicious intruders. But intrusion detection in vehicular networks is challenging because of its unique features of vehicular networks: short range wireless communication, large amount of nodes, and high mobility of nodes. Traditional methods are hard to detect intrusion in such sophisticated environment, especially when the attack pattern is unknown, therefore, it can result unacceptable false negative error rates. As a novel attempt, the main goal of this research is to apply data mining methodology to recognize known attacks and uncover unknown attacks in vehicular networks. We are the first to attempt to adapt data mining method for intrusion detection in vehicular networks. The main contributions include: 1) specially design a decentralized vehicle networks that provide scalable communication and data availability about network status; 2) applying two data mining models to show feasibility of automated intrusion detection system in vehicular networks; 3) find the detection patterns of unknown intrusions.

In vehicular ad hoc networks, the efficient and reliable dissemination of emergency messages in a highly mobile environment under dense or sparse network is a significant challenge. This paper proposes a new vehicular broadcast protocol, called ACK-CAST, that can operate effectively in both dense and sparse network scenarios. ACK-CAST relies on acknowledgment messages from one-hop neighbors to select the next rebroadcasting vehicle. Simulation results show that ACK-CAST outperforms the SERVUS protocol in terms of the end-to-end delay, message delivery ratio and network overhead.

Due to vehicle movement and lossy wireless channels, providing a reliable and efficient multi-hop broadcast service in vehicular ad hoc networks (VANETs) is a well-known challenging problem. In this paper, we propose BR-NB (broadcast with neighbor information), a fuzzy logic based multi-hop broadcast protocol for VANETs. BR-NB achieves a low overhead by using only a subset of neighbor nodes to relay data packets. For the relay node selection, BR-NB jointly considers multiple metrics of the inter-vehicle distance, vehicle mobility and link quality by employing fuzzy logic. Since the expected coverage and vehicle mobility are inferred from the two-hop neighbor information which can be acquired from the hello message exchange, BR-NB is independent of position information. BR-NB provides a practical and portable solution for broadcast services in VANETs. We use computer simulations and real-world experiments to evaluate the performance of BR-NB.

This paper proposes an efficient broadcast scheme based on traffic density measurement to mitigate broadcast storms in Vehicular Ad Hoc Networks (VANETs). In a VANET, the number of vehicles that rebroadcasts a message is closely related with the collision ratio of the message, so a well-designed broadcast scheme should consider traffic density when rebroadcasting a message. The proposed scheme introduces a traffic density measurement scheme and broadcast scheme for VANET. It is based on the slotted p-persistence scheme, but the rebroadcast procedure is enhanced and the rebroadcast probability p is controlled dynamically according to the estimated traffic density. Simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of the end-to-end delay and collision ratio.

In this letter, a Simple but Effective Congestion Control scheme (SECC) in VANET has been proposed to guarantee the successful transmissions for safety-related nodes. The strategy derive a Maximum Beacon Load Activity Indicator (MBLAI) to restrain the neighboring general periodical beacon load for the investigated safety-related “observation nodes”, i.e., the nodes associated with some emergent events. This mechanism actually reserves some bandwidth for the safety-related nodes to make them have higher priorities than periodical beacons to access channel. Different from the static congestion control scheme in IEEE802.11p, this strategy could provide dynamic control strength for congestion according to tolerant packets drop ratio for different applications.

We propose a Junction-Based Traffic Aware Routing (JTAR) protocol for Vehicular Ad Hoc Networks (VANETs) in sparse urban environments. A traffic aware optimum junction selection solution is adopted in packet-forwarding, and a metric named critical-segment is defined in recovery strategy. Simulation results show that JTAR can efficiently increase the packet delivery ratio and reduce the delivery delay.

Vehicular ad hoc networks have been attracting the interest of both academic and industrial communities on account of their potential role in Intelligent Transportation Systems (ITS). However, due to vehicle movement and fading in wireless communications, providing a reliable and efficient multi-hop broadcast service in vehicular ad hoc networks is still an open research topic. In this paper, we propose FUZZBR (FUZZy BRoadcast), a fuzzy logic based multi-hop broadcast protocol for information dissemination in vehicular ad hoc networks. FUZZBR has low message overhead since it uses only a subset of neighbor nodes to relay data messages. In the relay node selection, FUZZBR jointly considers multiple metrics of inter-vehicle distance, node mobility and signal strength by employing the fuzzy logic. FUZZBR also uses a lightweight retransmission mechanism to retransmit a packet when a relay fails. We use computer simulations to evaluate the performance of FUZZBR.

In the vehicular ad hoc network (VANET), broadcast is used to disseminate emergency warning messages (EWM) in public safety applications and delay is one of the most stringent requirements. Although flooding is the simplest broadcast scheme, it introduces a broadcast storm problem, and numerous broadcast protocols have been proposed for VANET in order to improve the performance of broadcast. In this letter, we analyze the tradeoff between two location-based broadcast protocols, i.e., distance-based relay selection (DBRS) and range-based relay selection (RBRS) schemes under various vehicular densities. Then, we propose a dynamic broadcast scheme, which selects an appropriate scheme from DBRS and RBRS, based on the estimation of vehicle density. The results of a performance analysis show that the proposed scheme dynamically selects the better scheme for varying vehicle density.

In Vehicular Ad hoc Networks (VANETs), general purpose ad hoc routing protocols such as AODV cannot work efficiently due to the frequent changes in network topology caused by vehicle movement. This paper proposes a VANET routing protocol QLAODV (Q-Learning AODV) which suits unicast applications in high mobility scenarios. QLAODV is a distributed reinforcement learning routing protocol, which uses a Q-Learning algorithm to infer network state information and uses unicast control packets to check the path availability in a real time manner in order to allow Q-Learning to work efficiently in a highly dynamic network environment. QLAODV is favored by its dynamic route change mechanism, which makes it capable of reacting quickly to network topology changes. We present an analysis of the performance of QLAODV by simulation using different mobility models. The simulation results show that QLAODV can efficiently handle unicast applications in VANETs.