A Simple and Robust Dissemination Protocol for VANETs

Several promising applications for Vehicular Ad-hoc Networks (VANETs) exist. For most of these applications, the communication among vehicles is envisioned to be based on the broadcasting of messages. This is due to the inherent highly mobile environment and importance of these messages to vehicles nearby. To deal with broadcast communication, dissemination protocols must be defined in such a way as to (i) prevent the so-called broadcast storm problem in dense networks and (ii) deal with disconnected networks in sparse topologies. In this paper, we present a Simple and Robust Dissemination (SRD) protocol that deals with these requirements in both sparse and dense networks. Its novelty lies in its simplicity and robustness. Simplicity is achieved by considering only two states (cluster tail and non- tail) for a vehicle. Robustness is achieved by assigning message delivery responsibility to multiple vehicles in sparse networks. Our simulation results show that SRD achieves high delivery ratio and low end-to-end delay under diverse traffic conditions

Exploiting traffic periodicity in industrial control networks

Industrial control systems play a major role in the operation of critical infrastructure assets. Due to the polling mechanisms typically used to retrieve data from field devices, industrial control network traffic exhibits strong periodic patterns. This paper presents a novel approach that uses message repetition and timing information to automatically learn traffic models that capture the periodic patterns. The feasibility of the approach is demonstrated using three traffic traces collected from real-world industrial networks. Two practical applications for the learned models are presented. The first is their use in intrusion detection systems; the learned models represent whitelists of valid commands and the frequencies at which they are sent; thus, the models may be used to detect data injection and denial-of-service attacks. The second application is to generate synthetic traffic traces, which can be used to test intrusion detection systems and evaluate the performance of industrial control devices

A directional data dissemination protocol for vehicular environments

This paper presents a simple and robust dissemination protocol that efficiently deals with data dissemination in both dense and sparse vehicular networks. Our goal is to address highway scenarios where vehicles equipped with sensors detect an event, e.g., a hazard and broadcast an event message to a specific direction of interest. In order to deal with broadcast communication under diverse network densities, we design a dissemination protocol in such a way that: (i) it prevents the so-called broadcast storm problem in dense networks by employing an optimized broadcast suppression technique; and (ii) it efficiently deals with disconnected networks by relying on the store-carry-forward communication model. The novelty of the protocol lies in its simplicity and robustness. Simplicity is achieved by only considering two states (i.e., cluster tail and non-tail) for vehicles. Furthermore, vehicles in both directions help disseminating messages in a seamlessly manner, without resorting to different operation modes for each direction. Robustness is achieved by assigning message delivery responsibility to multiple vehicles in sparse networks. Our simulation results show that our protocol achieves higher delivery ratio and higher robustness when compared with DV-CAST under diverse road scenarios