2,276 research outputs found

    Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET

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    In the last decade, cooperative vehicular network has been one of the most studied areas for developing the intelligent transportation systems (ITS). It is considered as an important approach to share the periodic traffic situations over vehicular ad hoc networks (VANETs) to improve efficiency and safety over the road. However, there are a number of issues in exchanging traffic data over high mobility of VANET, such as broadcast storms, hidden nodes and network instability. This paper proposes a new model to detect the traffic conditions using clustering traffic situations that are gathered from the nodes (vehicles) in VANET. The model designs new principles of multi-level clustering to detect the traffic condition for road users. Our model (a) divides the situations of vehicles into clusters, (b) designs a set of metrics to get the correlations among vehicles and (c) detects the traffic condition in certain areas. These metrics are simulated using the network simulator environment (NS-3) to study the effectiveness of the model

    Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

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    We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

    Study on QoS support in 802.11e-based multi-hop vehicular wireless ad hoc networks

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    Multimedia communications over vehicular ad hoc networks (VANET) will play an important role in the future intelligent transport system (ITS). QoS support for VANET therefore becomes an essential problem. In this paper, we first study the QoS performance in multi-hop VANET by using the standard IEEE 802.11e EDCA MAC and our proposed triple-constraint QoS routing protocol, Delay-Reliability-Hop (DeReHQ). In particular, we evaluate the DeReHQ protocol together with EDCA in highway and urban areas. Simulation results show that end-to-end delay performance can sometimes be achieved when both 802.11e EDCA and DeReHQ extended AODV are used. However, further studies on cross-layer optimization for QoS support in multi-hop environment are required

    TDMP-Reliable Target Driven and Mobility Prediction based Routing Protocol in Complex VANET

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    Vehicle-to-everything (V2X) communication in the vehicular ad hoc network (VANET), an infrastructure-free mechanism, has emerged as a crucial component in the advanced Intelligent Transport System (ITS) for special information transmission and inter-vehicular communications. One of the main research challenges in VANET is the design and implementation of network routing protocols which manage to trigger V2X communication with the reliable end-to-end connectivity and efficient packet transmission. The organically changing nature of road transport vehicles poses a significant threat to VANET with respect to the accuracy and reliability of packet delivery. Therefore, a position-based routing protocol tends to be the predominant method in VANET as they overcome rapid changes in vehicle movements effectively. However, existing routing protocols have some limitations such as (i) inaccurate in high dynamic network topology, (ii) defective link-state estimation (iii) poor movement prediction in heterogeneous road layouts. In this paper, a target-driven and mobility prediction (TDMP) based routing protocol is therefore developed for high-speed mobility and dynamic topology of vehicles, fluctuant traffic flow and diverse road layouts in VANET. The primary idea in TDMP is that the destination target of a driver is included in the mobility prediction to assist the implementation of the routing protocol. Compared to existing geographic routing protocols which mainly greedily forward the packet to the next-hop based on its current position and partial road layout, TDMP is developed to enhance the packet transmission with the consideration of the estimation of inter-vehicles link status, and the prediction of vehicle positions dynamically in fluctuant mobility and global road layout.Comment: 35 pages,16 Figure

    Routing And Communication Path Mapping In VANETS

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    Vehicular ad-hoc network (VANET) has quickly become an important aspect of the intelligent transport system (ITS), which is a combination of information technology, and transport works to improve efficiency and safety through data gathering and dissemination. However, transmitting data over an ad-hoc network comes with several issues such as broadcast storms, hidden terminal problems and unreliability; these greatly reduce the efficiency of the network and hence the purpose for which it was developed. We therefore propose a system of utilising information gathered externally from the node or through the various layers of the network into the access layer of the ETSI communication stack for routing to improve the overall efficiency of data delivery, reduce hidden terminals and increase reliability. We divide route into segments and design a set of metric system to select a controlling node as well as procedure for data transfer. Furthermore we propose a system for faster data delivery based on priority of data and density of nodes from route information while developing a map to show the communication situation of an area. These metrics and algorithms will be simulated in further research using the NS-3 environment to demonstrate the effectiveness
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