Impact of decentralized congestion control on contention-based forwarding in VANETs

Kuhlmorgen, Sebastian; Festag, Andreas; Fettweis, Gerhard

doi:10.1109/wowmom.2016.7523572

Cited by 20 publications

(11 citation statements)

References 10 publications

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“…The optimal setting of t wait depends on the congestion control mechanism as well as the current channel loads. Following the recommendations in [36,39], we choose t wait = 25 ms.…”

Section: Agent Hopping Algorithmmentioning

confidence: 99%

CarAgent: Collecting and disseminating floating car data in vehicular networks

Huang

Hassan

Geers

et al. 2018

Vehicular Communications

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Floating car data (FCD) refers to the motion and sensor data produced by moving vehicles on the road. Given that traffic management authorities and drivers can benefit from FCD enormously, there is an urgency to develop efficient FCD collection and dissemination techniques that scale with peak road traffic. In this paper, we present CarAgent, a message exchange protocol that periodically collects and uploads FCD to data centres with the minimal utilisation of existing mobile network resources. We also show how CarAgent can be easily extended to efficiently disseminate FCD to all vehicles in a target area using Dedicated Short Range Communication (DSRC), a recently released wireless communication standard for vehicles. We analytically derive the key performance metrics of CarAgent and validate them with simulations. We evaluate CarAgent using microscopic simulation of road traffic in real street maps while incorporating wireless protocol details of Long Term Evolution (LTE) and DSRC. Simulation results confirm that, compared to the state-of-the-art, CarAgent consumes 50% less LTE resources for FCD collection. For FCD dissemination, CarAgent consumes 45% less DSRC resources while improving the speed of dissemination significantly.

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“…The optimal setting of t wait depends on the congestion control mechanism as well as the current channel loads. Following the recommendations in [36,39], we choose t wait = 25 ms.…”

Section: Agent Hopping Algorithmmentioning

confidence: 99%

CarAgent: Collecting and disseminating floating car data in vehicular networks

Huang

Hassan

Geers

et al. 2018

Vehicular Communications

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“…CAMs are the other significant and safety message that carries acceleration, speed, direction, and position information. [13][14][15] One of the factors that make VANETs unreliable is the congestion problem, which leads to packet loss and a lower packet delivery ratio. 16 Various approaches have been proposed to cope with congestion problems.…”

Section: Introductionmentioning

confidence: 99%

“…One of them is the decentralized congestion control (DCC) approach that keeps the load of the communication channel below a limited threshold. 13 In the European system, DCCgatekeeper has been placed in a part of the protocol stack to control congestion more effectively. [13][14][15] DCCgatekeeper comprises four queues: the first, second, and third queues belong to DENM+, DENM, and CAM, respectively, whereas the fourth queue contains non-safety messages.…”

Section: Introductionmentioning

confidence: 99%

A traffic‐centric fuzzy approach for solving the starvation problem of cooperative awareness messages in vehicular ad hoc networks

Abdollah

Zarei

2021

Int J Communication

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Congestion problem in vehicular ad hoc networks (VANETs) is one of the main factors that negatively affect the inter-vehicle communication (IVC) efficiency of such emerging networks. Decentralized congestion control (DCC) is an effective method for overcoming the congestion problem. However, lower priority packets such as cooperative awareness messages (CAMs) may be encountered with the starvation problem in the DCC approach. This paper proposes FDCC: a traffic-centric Fuzzy DCC approach for improving CAMs delivery ratio, especially in congested traffic flows. FDDC architecture consists of four fuzzy inference systems (FISs). The inter-vehicle distance (IVD) and the speed variation are the spatiotemporal fuzzy inputs, which are customized for both single direction and multi-direction scenarios. Based on the FIS outputs, the FDCC control system, unlike the DCC, provides a way for processing starved CAMs by ignoring unnecessary even-driven messages. The obtained simulation results through OMNET++ in both single and multi-direction scenarios show the efficiency of FDCC in terms of the end-to-end delay, network throughput, and packet delivery ratio for event-driven messages as well as essential CAMs.

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“…Although IEEE 802.11p is the main standard for V2X communications, it can be challenged by high densities of users when transmitting multiple types of messages such as CAM and DENM, as well as other messages that are currently in standardization. Indeed, this multiplicity of messages pushes decentralized congestion control to its performance limits [5], [6]. The cellular technology Long Term Evolution (LTE) is emerging as new alternative for V2X communications.…”

Section: Introductionmentioning

confidence: 99%

Channel Models for the Simulation of Different RATs Applied to Platoon Emergency Braking

Nan

Jornod

Schweins

et al. 2019

2019 European Conference on Networks and Communications (EuCNC)

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We analyze the performance of different channel models and Radio Access Technologies (RATs) for platoon emergency braking in a highway scenario. We present a ray tracing channel model and analyze its differences with the WINNER+ stochastic channel model in terms of the pathloss calculation. Thanks to the consideration of obstacles and their reflections, the ray tracing channel model has been shown to be more realistic in near Tx-Rx distance. This corroborates the results of our performance comparison which highlights larger differences in close Tx-Rx pairs. Considering the simulation time consumption and the more realistic ray tracing predictions, we propose a new models usage for our simulations: a combination of WINNER+ and ray tracing channel models. Moreover, we implement one new 5G numerology on the basis of Long Term Evolution-Vehicles (LTE-V) for Vehicle-to-everything (V2X) communications. We include this new feature in our benchmarking setup and provide performance analysis results. It provides a basis for our future research of further 5G components.

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Impact of decentralized congestion control on contention-based forwarding in VANETs

Cited by 20 publications

References 10 publications

CarAgent: Collecting and disseminating floating car data in vehicular networks

CarAgent: Collecting and disseminating floating car data in vehicular networks

A traffic‐centric fuzzy approach for solving the starvation problem of cooperative awareness messages in vehicular ad hoc networks

Channel Models for the Simulation of Different RATs Applied to Platoon Emergency Braking

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