Securing Warning Message Dissemination in VANETs using Cooperative Neighbor Position Verification

Efficient schemes for warning message dissemination in vehicular ad hoc networks (VANETs) use context information collected by vehicles about their neighbor nodes to guide the dissemination process. Based on this information, vehicles autonomously decide whether they are the most appropriate forwarding nodes. These schemes maximize their performance when all the vehicles advertise correct information about their positions, but position errors may drastically reduce the performance of the dissemination process. We present a proactive cooperative neighbor position verification protocol that detects nodes advertising false locations and selects optimal forwarders to mitigate the impact of adversarial users. We combine our mechanism with two warning dissemination schemes for VANETs and demonstrate how the latter can benefit from the use of our security scheme in the presence of malicious nodes trying to exploit known system vulnerabilities

Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

Detecting Non-Line of Sight to Prevent Accidents in Vehicular Ad hoc Networks

There are still many challenges in the field of VANETs that encouraged researchers to conduct further investigation in this field to meet these challenges. The issue pertaining to routing protocols such as delivering the warning messages to the vehicles facing Non-Line of Sight (NLOS) situations without causing the storm problem and channel contention, is regarded as a serious dilemma which is required to be tackled in VANET, especially in congested environments. This requires the designing of an efficient mechanism of routing protocol that can broadcast the warning messages from the emergency vehicles to the vehicles under NLOS, reducing the overhead and increasing the packet delivery ratio with a reduced time delay and channel utilisation. The main aim of this work is to develop the novel routing protocol for a high-density environment in VANET through utilisation of its high mobility features, aid of the sensors such as Global Positioning System (GPS) and Navigation System (NS). In this work, the cooperative approach has been used to develop the routing protocol called the Co-operative Volunteer Protocol (CVP), which uses volunteer vehicles to disseminate the warning message from the source to the target vehicle under NLOS issue; this also increases the packet delivery ratio, detection of NLOS and resolution of NLOS by delivering the warning message successfully to the vehicle under NLOS, thereby causing a direct impact on the reduction of collisions between vehicles in normal mode and emergency mode on the road near intersections or on highways. The cooperative approach adopted for warning message dissemination reduced the rebroadcast rate of messages, thereby decreasing significantly the storm issue and the channel contention. A novel architecture has been developed by utilising the concept of a Context-Aware System (CAS), which clarifies the OBU components and their interaction with each other in order to collect data and take the decisions based on the sensed circumstances. The proposed architecture has been divided into three main phases: sensing, processing and acting. The results obtained from the validation of the proposed CVP protocol using the simulator EstiNet under specific conditions and parameters showed that performance of the proposed protocol is better than that of the GRANT protocol with regard to several metrics such as packet delivery ratio, neighbourhood awareness, channel utilisation, overhead and latency. It is also successfully shown that the proposed CVP could detect the NLOS situation and solves it effectively and efficiently for both the intersection scenario in urban areas and the highway scenario

Information collection algorithm for vehicular ad-hoc networks (application domain: Urban Traffic Wireless Vehicular Ad-Hoc Networks (VANETs))

Vehicle to vehicle communication (V2VC) is one of the modern approaches for exchanging and generating traffic information with (yet to be realized) potential to improve road safety, driving comfort and traffic control. In this research, we present a novel algorithm which is based on V2V communication, uses in-vehicle sensor information and in collaboration with the other vehicles' sensor information can detect road conditions and determine the geographical area where this road condition exists – e.g. geographical area where there is traffic density, unusual traffic behaviour, a range of weather conditions (raining), etc. The algorithms' built-in automatic geographical restriction of the data collection, aggregation and dissemination mechanisms allows warning messages to be received by any car, not necessarily sharing the identified road condition, which may then be used to identify the optimum route taken by the vehicle e.g. avoid bottlenecks or dangerous areas including accidents or congestions on their current routes. This research covers the middle ground between MANET [1] and collaborative data generation based on knowledge granularity (aggregation). It investigates the possibility of designing, implementing and modelling of the functionality of an algorithm (as part of the design of an intelligent node in an Intelligent Transportation System - ITS) that ensures active participation in the formation, routing and general network support of MANETs and also helps in-car traffic information and real-time control generation and distribution. The work is natural extension of the efforts of several large EU projects like DRIVE [2], GST [3] and SAFESPOT [4]