Vehicular networking and channel modeling: A new Markovian approach

Fazio, Peppino; Tropea, Mauro; Sottile, Cesare; Lupia, Andrea

doi:10.1109/ccnc.2015.7158064

Cited by 19 publications

(8 citation statements)

References 11 publications

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“…We have developed this network which manages to improve the establishment of the wireless network connection of mobile users in highly dynamic scenarios. We observed that the standard Network Manager is not suitable for these environments since it decides to stay on a network even if the signal strength is very poor [19]. Moreover, when it gets to a total disconnection it keeps trying to reestablish the previous connection, even if it is not available in the current location.…”

Section: The Signalbased Managermentioning

confidence: 99%

Improving MQTT Data Delivery in Mobile Scenarios: Results from a Realistic Testbed

Luzuriaga

Pérez

Boronat

et al. 2016

Mobile Information Systems

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MQTT is being widely used for data delivery in IoT applications but its architecture does not properly handle mobility when disconnection periods tend to be large. In this paper we describe an experimental evaluation, made in a real environment, of a solution that guarantees that there is no information loss when variable length hand-offs appear due to the movement of a node. Our proposal modifies the classical publish/subscribe scheme by introducing an intermediate buffer that takes care of message transfer. Finally, we study the impact related to the connectivity of mobile devices of the use of the standard LinuxNetwork Manager. We propose a cross-layer solution that improves the device connectivity in conjunction with the data layer management. We show that our solution improves the data delivery guaranteeing that no information is lost.

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Section: The Signalbased Managermentioning

confidence: 99%

Improving MQTT Data Delivery in Mobile Scenarios: Results from a Realistic Testbed

Luzuriaga

Pérez

Boronat

et al. 2016

Mobile Information Systems

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“…The link between the various states can be expressed through a Markov chain with as many states as there are different statistical models; therefore, the switching process between the various channel models is described with the Markov chain. The use of a Markov channel model is an approach used for different types of wireless networks [26], such as underwater acoustic channel communications [27,28], ultra wideband (UWB) networks [29], and vehicle ad hoc networks [30].…”

Section: Lms Channel Modelsmentioning

confidence: 99%

A Comprehensive Review of Channel Modeling for Land Mobile Satellite Communications

Tropea

Rango

2022

Electronics

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As demands on the network continue to grow, it is increasingly important to upgrade the existing infrastructure in order to offer higher bandwidth and service level guarantees to users. Next generation networks (NGNs) represent a fully IP-based architecture that is able to support different technologies. In this context, the satellite networks are considered a fundamental part for future hybrid architectures. In this scenario, knowing satellite channel propagation characteristics in order to be able to design a communication system to respond to new user needs is of fundamental importance. Many papers in the literature show channel models in different satellite scenarios both for fixed and mobile applications; however, to the best of our knowledge, nobody presents an overview on different satellite models based on Markov chains. This paper wants to present a comprehensive review of the most recent developments in satellite channel communications related to mobile services and, in particular, for the land mobile satellite systems. The work presents all different types of Markov models, from single-state to multi-state models, that have been proposed in the literature from the early 1980s.

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“…The Markovian routing approach combines Markovian Traffic Equilibrium (MTE) with the Network Utility Maximization (NUM) model to form a Markovian Network Utility Maximization (MNUM) [125]. It establishes the uniqueness of equilibrium which allows providing a design for congestion control with multipath routing.…”

Section: Markovian Routingmentioning

confidence: 99%

A survey on congestion detection and control in connected vehicles

2020

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The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications.

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Vehicular networking and channel modeling: A new Markovian approach

Cited by 19 publications

References 11 publications

Improving MQTT Data Delivery in Mobile Scenarios: Results from a Realistic Testbed

Improving MQTT Data Delivery in Mobile Scenarios: Results from a Realistic Testbed

A Comprehensive Review of Channel Modeling for Land Mobile Satellite Communications

A survey on congestion detection and control in connected vehicles

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