Ramon S. Schwartz

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.

A scalable data dissemination protocol for both highway and urban vehicular environments

Vehicular ad hoc networks (VANETs) enable the timely broadcast dissemination of event-driven messages to interested vehicles. Especially when dealing with broadcast communication, data dissemination protocols must achieve a high degree of scalability due to frequent deviations in the network density. In dense networks, suppression techniques are designed to prevent the so-called broadcast storm problem. In sparse networks, protocols incorporate store-carry-forward mechanisms to take advantage of the mobility of vehicles to store and relay messages until a new opportunity for dissemination emerges. Despite numerous efforts, most related works focus on either highway or urban scenarios, but not both. Highways are mostly addressed with a single directional dissemination. For urban scenarios, protocols mostly concentrate on either using infrastructure or developing methods for selecting vehicles to perform the store-carry-forward task. In both cases, dense networks are dealt with suppression techniques that are not optimal for multi-directional dissemination. To fill this gap, we present an infrastructure-less protocol that combines a generalized time slot scheme based on directional sectors and a store-carry-forward algorithm to support multi-directional data dissemination. By means of simulations, we show that our protocol scales properly in various network densities in both realistic highway and urban scenarios. Most importantly, it outperforms state-of-the-art protocols in terms of delivery ratio, end-to-end delay, and number of transmissions. Compared to these solutions, our protocol presents up to seven times lower number of transmissions in dense highway scenarios.

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.

On the applicability of fair and adaptive data dissemination in traffic information systems

Vehicular Ad hoc Networks (VANETs) are expected to serve as support to the development of not only safety applications but also information-rich applications that disseminate relevant data to vehicles. Due to the continuous collection, processing, and dissemination of data, one crucial requirement is the efficient use of the available bandwidth. Firstly, the rate of message transmissions must be properly controlled in order to limit the amount of data inserted into the network. Secondly, messages must be carefully selected to maximize the utility (benefit) gain of vehicles in the neighborhood. We argue that such selection must aim at a fair distribution of data utility, given the possible conflicting data interests among vehicles. In this work, we propose a data dissemination protocol for VANETs that distributes data utility fairly over vehicles while adaptively controlling the network load. The protocol relies only on local knowledge to achieve fairness with concepts of Nash Bargaining from game theory. We show the applicability of the protocol by giving example of utility functions for two Traffic Information Systems (TIS) applications: (i) parking-related and (ii) traffic information applications. The protocol is validated with both real-world experiments and simulations of realistic large-scale networks. The results show that our protocol presents a higher fairness index and yet it maintains a high level of bandwidth utilization efficiency compared to other approaches.

Fair and adaptive data dissemination for Traffic Information Systems

Vehicular Ad-hoc Networks (VANETs) are expected to serve as support to the development of not only safety applications but also information-rich applications that disseminate relevant data to vehicles. Due to the continuous collection, processing, and dissemination of data, one crucial requirement is the efficient use of the available bandwidth. Firstly, the rate of message transmissions must be properly controlled in order to limit the amount of data inserted into the network. Secondly, messages must be carefully selected to maximize the utility (benefit) gain of vehicles in the neighborhood. We argue that such selection must aim at a fair distribution of data utility, given the possible conflicting data interests among vehicles. In this work, we propose a data dissemination protocol for VANETs that distributes data utility fairly over vehicles while adaptively controlling the network load. The protocol relies only on local knowledge to achieve fairness with concepts of Nash Bargaining from game theory. Simulation results show that our algorithm presents a higher fairness index and yet it maintains a high level of bandwidth utilization efficiency compared to other approaches. In addition, the rate of transmissions is adaptively controlled as new information about the environment is collected.

Achieving Data Utility Fairness in Periodic Dissemination for VANETs

In addition to safety, Vehicular Ad-hoc Networks (VANETs) enable the development of new information-rich applications that disseminate relevant data to vehicles. One key challenge in such networks is to use the available bandwidth efficiently when there is: (i) a short connectivity time due to the rapidly changing road environment, and (ii) bandwidth congestion due to continuous collection and dissemination of data. Numerous solutions were proposed to alleviate bandwidth congestion by using transmission power and beaconing rate control. However, the reduction of data messages transmitted by using priority- based data selection mechanisms has not been fully explored. In this work, we propose a periodic data dissemination protocol for non-safety applications which distributes data utility fairly among vehicles with conflicting data interests. Furthermore, given a defined maximum network load allowed, only the least relevant data is suppressed. Fairness is achieved using the concept of Nash Bargaining from game theory. Simulation results show that our approach leads to an efficient bandwidth utilization in terms of utility per message received and higher fairness index compared with other approaches.

Towards opportunistic sensed data dissemination in vehicular environments

This paper proposes guidelines for the design of dissemination protocols for data sensed in vehicular environments in view of a number of potential applications. We organize the data dissemination process in three main tasks: discovery, assessment, and seizing of data exchange opportunities. One major problem is the limitation in bandwidth due to large amounts of data and short communication time slots. We elaborate on this problem by presenting preliminary results which favor an approach which disseminate date fairly over the nodes in the network.