Information Dissemination In Vehicular Networks Research Articles

Non-Orthogonal Age-Optimal Information Dissemination in Vehicular Networks: A Meta Multi-Objective Reinforcement Learning Approach

Non-Orthogonal Age-Optimal Information Dissemination in Vehicular Networks: A Meta Multi-Objective Reinforcement Learning Approach

A V2I BASED APPROACH TO MULTICAST IN VEHICULAR NETWORKS

The present research work proposes a novel approach for efficient information dissemination in Vehicular Networks using V2I based communication. This approach makes use of the V2I communication to establish the connectivity between the cloud server and the vehicle. The approach is focused on finding the utility of existing IoT protocols in the Vehicular Networks. The foundation of this work relies in the (Message Queue Telemetry Transport Protocol) MQTT protocol, IoT and IaaS. The paper presents the background technologies used in the work and propose the approach. The proposed approach has been experimentally tested and found significant results.

Efficient Information Dissemination in Vehicular Networks with Topological Approach

Efficient Information Dissemination in Vehicular Networks with Topological Approach

A Context-Aware Trust-Based Information Dissemination Framework for Vehicular Networks

Reliable, secure, private, and fast communication in vehicular networks is extremely challenging due to the highly mobile nature of these networks. Contact time between vehicles is very limited and topology is constantly changing. Trusted communication in vehicular networks is of crucial importance because without trust, all efforts for minimizing the delay or maximizing the reliability could be voided. In this paper, we propose a trust-based framework for a safe and reliable information dissemination in vehicular networks. The proposed framework consists of two modules such that the first one applies three security checks to make sure the message is trusted. It assigns a trust value to each road segment and one to each neighborhood, instead of each car. Thus, it scales up easily and is completely distributed. Once a message is evaluated and considered to be trustworthy, our method then in the second module looks for a safe path through which the message is forwarded. Our frameworks are application-centric; in particular, it is capable of preserving traffic requirements specified by each application. Experimental results demonstrate that this framework outperforms other well-known routing protocols since it routes the messages via trusted vehicles.

Probabilistic deployment of dissemination points in urban areas to support vehicular communication

This work presents a probabilistic constructive heuristic to support the design of roadside infrastructure for information dissemination in vehicular networks. We formulate this as a Probabilistic Maximum Coverage Problem (PMCP) and we intend to maximize the number of vehicles that get in contact with the infrastructure. We compare our approach with non-probabilistic MCP in simulated urban areas following a Manhattan-style topology with variable traffic conditions. The main contributions of this work are (i) the formal definition of the Probabilistic Maximum Coverage Problem, (ii) the application of PMCP to solve one instance of the problem of facilities allocation and (iii) the application of a probabilistic approach to model the volume of vehicles along the urban area, where the position of each vehicle is no longer considered deterministic, but it is treated as a probability function distributed over all the intersections. The vehicles no longer have a position. Instead, vehicles have a probability of being in a given position at a given instant of time. The results reveal that PMCP requires less dissemination points (DPs) to achieve similar coverage ratio than non-probabilistic MCP, while preserving the same samples deviation. Keywords: vehicular networks, maximum coverage problem, information dissemination.