Transmit Data Rate Control Based Decentralized Congestion Control Mechanism for VANETs

Patil, Ashish; Deeksha, M; Shekar, N. Chandra; Shet, Vinayaka B.; Kulkarni, Muralidhar

doi:10.1109/icondsc.2019.8816902

Cited by 10 publications

(8 citation statements)

References 7 publications

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“…In vehicular networks, data management refers to the application of methods to manage data of interest to drivers, including suitable mechanisms for retrieving and transferring data, specific data filtering, the handling of data queries, data collection, and efficient data exploitation while attempting to avoid possible risks. [39][40][41][42][43][44][45][46][47][48][49][51][52][53][54][55][58][59][60][65][66][67][68] Researchers in congestion control-enabled data management domain in VANETs and IoV networks focus more on solving challenges such as improving network performance 48,60,65 , better RT 42,66 , strengthening PDR 67,68 , simplifying throughput 51,58,67,68 , better E2E delay 39,40,43,48,67,68 , increasing channel utilization 44,67 , reducing communication costs 39,40 , reducing the average WT 41,…”

Section: Data Managementmentioning

confidence: 99%

“…VANETs and IoV networks place a high priority on data management, wherein network nodes continually create, collect, or propagate data with details about their position and the time it was stored, which is then processed locally in each vehicle's internal processors. In vehicular networks, data management refers to the application of methods to manage data of interest to drivers, including suitable mechanisms for retrieving and transferring data, specific data filtering, the handling of data queries, data collection, and efficient data exploitation while attempting to avoid possible risks 39–49,51–55,58–60,65–68 . Researchers in congestion control‐enabled data management domain in VANETs and IoV networks focus more on solving challenges such as improving network performance 48,60,65 , better RT 42,66 , strengthening PDR 67,68 , simplifying throughput 51,58,67,68 , better E2E delay 39,40,43,48,67,68 , increasing channel utilization 44,67 , reducing communication costs 39,40 , reducing the average WT 41,52 , and effective use of resources and reducing casualties in congested areas.…”

Section: Organization Of Congestion Control In Iov and Vanetsmentioning

confidence: 99%

“…Patil et al 54 devised a distributed congestion management approach based on multistate active transmit data rate monitoring. For the simulation, the realistic situation developed by SUMO was taken into account.…”

Section: Organization Of Congestion Control In Iov and Vanetsmentioning

confidence: 99%

See 2 more Smart Citations

A systematic review of congestion control in internet of vehicles and vehicular ad hoc networks: Techniques, challenges, and open issues

Hemmati,

Zarei,

Rahmani

2023

Int J Communication

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SummaryThe Internet of Vehicles (IoV) integrates various technologies to enable real‐time data exchange between vehicles, pedestrians, roadside units, unmanned aerial vehicles, road‐added things, and so forth. IoV is an improved internet‐enabled vehicular ad hoc network (VANET), which is similarly affected by data traffic aggravated by time‐variant network density and the network's topological and informational changes. A high density of simultaneous vehicular communication leads to channel saturation and data congestion, which leads to rapid increases in data loss, packet latency, and lower service quality. Due to the importance of real‐time data communications in high dynamic networks, we used the systematic literature review (SLR) approach to identify 54 articles up to May 2023 to discuss the ways to deal with data traffic congestion in VANETs and IoV networks as well as existing and upcoming issues in this area.

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Section: Data Managementmentioning

confidence: 99%

Section: Organization Of Congestion Control In Iov and Vanetsmentioning

confidence: 99%

See 1 more Smart Citation

A systematic review of congestion control in internet of vehicles and vehicular ad hoc networks: Techniques, challenges, and open issues

Hemmati,

Zarei,

Rahmani

2023

Int J Communication

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“…A multi-state active transmit data rate control mechanism based on DCC has been introduced in [13]. Here the channel load is calculated according to the CBR of the network and a multi-state active DCC protocol chooses the data rate according to the recent channel load.…”

Section: Related Workmentioning

confidence: 99%

Increasing vehicles perception using cooperative relaying and priority-based beaconing

Faiz¹,

Achir

Boussetta³

2021

2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR)

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The use of vehicle's on-board sensors in increasing the perception of cooperative vehicles is becoming prevailing and essential for the road safety. However trusting only on the on-board sensors could limit the perception of the cooperative vehicles for example an object/vehicle can not be detected if it is impeded by some obstruction. The perception efficiency of vehicles can be increased beyond their field of view (FoV) by exchanging the sensor detected information through V2X communication. The perception of vehicles can be more accurate as much as frequent they share the information. However by transmitting numerous messages could saturate the communication channel and deteriorate the perception improvement specially in the dense circumstances. In this paper we address both these issues and propose two different schemes, (i) an information propagating mechanism to increase the cooperative vehicle's perception above their FoV and (ii) an optimal dynamic cooperative priority based beaconing model to coup with the channel congestion. By using the information propagation mechanism we can increase the perception of cooperative vehicles up to their maximum communication range and on the other end probability based dynamic cooperative priority beaconing scheme selects the most suitable cooperative vehicle to transmit based on its on-board sensor facility. These proposed mechanisms immensely decrease the contention on the channel while extend the perception beyond the FoV. We evaluate both the mechanisms for the performance in terms of vehicles awareness, channel load and communication range through simulations for several vehicle densities. The simulation results show that these proposals provide better performance compare to the classical beaconing schemes.

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“…The authors of [17] proposed a multi-state active transmit data rate control mechanism based on DCC. In this mechanism, channel load is calculated in terms of CBR, and the multi-state active DCC protocol adopts data rate according to the currently available channel load.…”

Section: Related Workmentioning

confidence: 99%

On the benefits of increased vehicles perception to cooperative communications

Faiz

Achir

Boussetta

2020

Proceedings of the ACM MobiArch 2020 the 15th Workshop on Mobility in the Evolving Internet Architecture

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Intelligent Transportation Systems (ITS) are expected to play a vital role in increasing road safety and road efficiency in the near future. The primary feature of ITS applications is to provide road safety, which is based on IEEE-802.11p technology, by transmitting safety messages to the vehicles in the surrounding. The channel congestion is a significant challenge for the IEEE802.11p, ITS is operating on. Congestion increases the data loss and degrades the ITS performance resulting from compromising passengers safety. In this paper, we analyze the benefits of exploiting vehicle's embedded sensors to enhance car perception and hence improve the efficiency of cooperative communications. To this purpose, we implemented the collaborative environment perception approach for vehicular safety applications proposed by [1] and analyze its performance and behavior in congested urban traffic. In this proposal, so-called ECAM (Extended Cooperative Awareness Message), vehicles use a different type of sensors (cameras, radars, lidars etc.) to collect the status information of the surrounding vehicles in their detection range and share this information through a collaborative beaconing scheme to reduce congestion on the communication channel. This scheme implements a dual step mechanism to function. The first phase implements the collaborative perception mechanism by adding the locally collected information in the safety message and sharing this up to date data to intensify the awareness among the vehicles in its communication surrounding. In the second phase, the recipient vehicles verify the accuracy of the information received from the collective perception enabled vehicles by leveraging the position by adding an error threshold. Performance evaluation conducted through extensive simulations shows the benefits of exploiting increased perception to enhance awareness among cars while reducing the contention on the wireless interface.

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Transmit Data Rate Control Based Decentralized Congestion Control Mechanism for VANETs

Cited by 10 publications

References 7 publications

A systematic review of congestion control in internet of vehicles and vehicular ad hoc networks: Techniques, challenges, and open issues

A systematic review of congestion control in internet of vehicles and vehicular ad hoc networks: Techniques, challenges, and open issues

Increasing vehicles perception using cooperative relaying and priority-based beaconing

On the benefits of increased vehicles perception to cooperative communications

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