AN ADAPTIVE INFORMATION DISSEMINATION MODEL FOR VANET COMMUNICATION

Vehicular ad hoc networks (VANETs) have been envisioned to be useful in road safety and many commercial applications. The growing trend to provide communication among the vehicles on the road has provided the opportunities for developing a variety of applications for VANET. The unique characteristics of VANET bring about new research challenges

Design and analysis of a beacon-less routing protocol for large volume content dissemination in vehicular ad hoc networks

Largevolumecontentdisseminationispursuedbythegrowingnumberofhighquality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors’ best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well

The Reputation of Machine Learning in Wireless Sensor Networks and Vehicular Ad Hoc Networks

It's difficult to deal with the dynamic nature of VANETs and WSNs in a way that makes sense. Machine learning (ML) is a preferred method for dealing with this kind of dynamicity. It is possible to define machine learning (ML) as a way of dealing with heterogeneous data in order to get the most out of a network without involving humans in the process or teaching it anything. Several techniques for WSN and VANETs based on ML are covered in this study, which provides a fast overview of the main ML ideas. Open difficulties and challenges in quickly changing networks, as well as diverse algorithms in relation to ML models and methodologies, are also covered in the following sections. We've provided a list of some of the most popular machine learning (ML) approaches for you to consider. As a starting point for further research, this article provides an overview of the various ML techniques and their difficulties. This paper's comparative examination of current state-of-the-art ML applications in WSN and VANETs is outstanding

Design of an adaptive congestion control protocol for reliable vehicle safety communication

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Exploration of Adaptive Beaconing for Efficient Intervehicle Safety Communication

In the future intervehicle communication will make driving safer, easier, and more comfortable. As a cornerstone of the system, vehicles need to be aware of other vehicles in the vicinity. This cooperative awareness is achieved by beaconing, the exchange of periodic single-hop broadcast messages that include data on the status of a vehicle. While the concept of beaconing has been developed in the first phase of research on VANETs, recent studies have revealed limitations with respect to network performance. Obviously, the frequency of beacon messages directly translates into accuracy of cooperative awareness and thus traffic safety. There is an indisputable trade-off between required bandwidth and achieved accuracy. In this work we analyze this trade-off from different perspectives considering the consequences for safety applications. As a solution to the problem of overloading the channel, we propose to control the offered load by adjusting the beacon frequency dynamically to the current traffic situation while maintaining appropriate accuracy. To find an optimal adaptation, we elaborate on several options that arise when determining the beacon frequency. As a result, we propose situation-adaptive beaconing. It depends on the vehicle's own movement and the movement of surrounding vehicles, macroscopic aspects like the current vehicle density, or microscopic aspects

Supporting Protocols for Structuring and Intelligent Information Dissemination in Vehicular Ad Hoc Networks

The goal of this dissertation is the presentation of supporting protocols for structuring and intelligent data dissemination in vehicular ad hoc networks (VANETs). The protocols are intended to first introduce a structure in VANETs, and thus promote the spatial reuse of network resources. Segmenting a flat VANET in multiple cluster structures allows for more efficient use of the available bandwidth, which can effectively increase the capacity of the network. The cluster structures can also improve the scalability of the underlying communication protocols. The structuring and maintenance of the network introduces additional overhead. The aim is to provide a mechanism for creating stable cluster structures in VANETs, and to minimize this associated overhead. Further a hybrid overlay-based geocast protocol for VANETs is presented. The protocol utilizes a backbone overlay virtual infrastructure on top of the physical network to provide geocast support, which is crucial for intervehicle communications since many applications provide group-oriented and location-oriented services. The final contribution is a structureless information dissemination scheme which creates a layered view of road conditions with a diminishing resolution as the viewing distance increases. Namely, the scheme first provides a high-detail local view of a given vehicle\u27s neighbors and its immediate neighbors, which is further extended when information dissemination is employed. Each vehicle gets aggregated information for road conditions beyond this extended local view. The scheme allows for the preservation of unique reports within aggregated frames, such that safety critical notifications are kept in high detail, all for the benefit of the driver\u27s improved decision making during emergency scenarios