A Delay Sensitive Bus-based Routing Technique for Urban Vehicular Networks

Kerkacha, Nabil; Hadj-Said, Naima; Chaib, Noureddine; Adnane, Asma; Ali-Pacha, Adda

doi:10.1109/ccssp49278.2020.9151466

Cited by 1 publication

(2 citation statements)

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“…It uses knowledge of the predictable and periodic movements of buses to learn the temporal distance to transmit every piece of data to RSUs using a dedicated busbased foundation. The authors of [140] propose a superior form of BRT and use simulations to show the performance improvement achieved.…”

Section: B Uncertain Node Mobilitymentioning

confidence: 99%

“…Contributions [47] The proposed routing protocol has the ability to learn the best suited transmission parameters from interactions with the environment [45] Uses knowledge of predictable and periodic movement of buses to learn the temporal distance to transmit every data to RSUs [140] Proposes a better form of BRT which results in overall performance improvement of bus-based routing [51] A group-based routing approach is proposed for detecting the position in 3D for beam selection in mmWave-based V2X transmissions mobility models to learn about vehicle mobility and analyze the impact of mobility on VANET performance. The performance of these models is recorded and correlated using suitable mobility metrics, as they play a very important role in network design.…”

Section: Itemmentioning

confidence: 99%

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A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Chatterjee¹,

Karmakar

Kaddoum

et al. 2022

IEEE Access

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Intelligent transportation systems (ITSs) have become increasingly popular because they support effective coordination in connected vehicles. ITSs present an integrated approach for exchanging relevant information in order to improve the safety, efficiency, and reliability of road transportation systems. A variant of mobile ad-hoc networks (MANETs) called vehicular ad-hoc networks (VANETs) are an integral component of ITSs. VANETs consist of interconnected vehicles with sensing abilities that exchange information related to traffic, positioning, weather, and emergency services. In general, vehicle-to-everything (V2X) refers to communications between any entity and a vehicle, where the entity may be a vehicle, a cloud-based network, a pedestrian, or equipment installed along a road. One of the crucial challenges in V2X is the reliable and timely circulation of information among vehicular nodes to allow drivers to make decisions that increase road safety. In this context, efficient V2X routing protocols play a key role in supporting reliability and safety, and enhancing the overall quality of service (QoS) in VANETs. However, VANETs have distinct characteristics, such as high vehicular node mobility, unsteady connectivity, rapid changes in network topology, and unbounded network size, that can significantly affect routing in the network. Various routing protocols for V2X communication exist in the open technical literature. In this survey, we categorize the routing mechanisms as non-learning-and learning-based approaches, and discuss existing V2X routing protocols and their contributions to and impacts on VANET performance. Here, the learning-based approach implies the use of machine learning algorithms. This survey also summarizes open challenges in designing effective V2X routing protocols and future research directions to consider when developing smart routing mechanisms for next-generation intelligent VANET technologies.INDEX TERMS VANET, V2X, routing protocol, non-learning-based routing, learning-based routing.

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Section: B Uncertain Node Mobilitymentioning

confidence: 99%