Improving dynamic and distributed congestion control in vehicular ad hoc networks

Cao

International Journal of Distributed Sensor Networks

et al. 2018

Internet of Vehicles has become a promising way to realize the evolution from vehicular ad hoc networks and nextgeneration intelligent transportation system into future autonomous driving scenarios, clean-energy intelligent vehicles, and Smart Cities. However, multicasting service messages on available service channels and periodic exchanges of beacon messages on control channel cause the problem of efficiently scheduling those messages via multichannel transmission for intelligent vehicle terminal, to support real-world applications in Internet of Vehicles scenario. In this article, we investigate the intelligent vehicle terminal architecture and, particularly, design the wireless communication board by incorporating multicasting and congestion control modules. Especially, we present a multicast data delivery scheme with random-delay lowest-cost constraint to transfer service messages on service channels. Furthermore, a priority-aware congestion control scheme is also proposed by considering differentiated priorities of beacon messages on control channel, to cope with the congestion problem at bottleneck vehicle node. Based on the proposed schemes, we build up the RanLow (Random-delay Lowest-cost) module and the priority-aware congestion control (PARCEL) module by enabling multicasting and congestion control together in wireless communication board of the intelligent vehicle terminal architecture. Finally, the experimental results and comparison show that our devised RanLow module and PARCEL module are feasible and more efficient than existing schemes.

Section: Discussionmentioning

confidence: 99%

Section: Problem and Motivationmentioning

confidence: 99%

MAC²: Enabling multicasting and congestion control with multichannel transmission for intelligent vehicle terminal in Internet of Vehicles

Cao

International Journal of Distributed Sensor Networks

et al. 2018

Trans Emerging Tel Tech

“…Taherkhani and Pierre proposed a centralized and localized data congestion control strategy that includes detecting congestion, clustering messages, and controlling data congestion. The quality of transceiver channel is estimated to perceive the congested data in the channels.…”

Section: Analysis Of Handover Failures In Vanetmentioning

confidence: 99%

“…Taherkhani and It proposed a centralized and localized It spent long handover latency in Pierre 52,53 data congestion control strategy that dynamic VANET due to the includes detecting congestion, high mobility of the vehicles and clustering messages, and controlling high frequency of topology variations. data congestion.…”

Section: Approaches Features Limitationsmentioning

confidence: 99%

A comprehensive survey on handover management for vehicular ad hoc network based on 5G mobile networks technology

Ahmed

Alzahrani

2018

Vehicular ad hoc network (VANET) is a style of high‐mobility mobile ad hoc network where the mobile nodes are vehicles traveling across a road or a street. VANET was proposed to provide safety, comfortability, reliability, and security of vehicles driving. One of the serious challenges is handover (HO) problem that occurs when a vehicle moves from one network area covered by a roadside unit (RSU) to another network area covered by a different RSU. The fast mobility of vehicles and the limited coverage area of the RSU (without overlapping signals) should be considered in providing a seamless HO. This paper presents a comprehensive survey on HO management for VANET based on the new features of fifth‐generation (5G) mobile network technologies. The 5G mobile network technology provides enhanced characteristics that will fit the requirements of real‐time video streaming and assist to design an effective solution for the HO problem. In addition, this paper presents the reasons for HO failures and the limitations of available HO failure solutions. Furthermore, it highlights the potential proposed solutions that will tackle the HO failures. This survey will open up the gate of developing an optimal solution based on 5G for HO problem on VANET that might be used in vehicles manufacturing.

Wireless Communications and Mobile Computing

“…In [19], Garg et al evaluate the performance of a data delivery mechanism for Vehicular Ad Hoc Networks and Cognitive Radio (CR) Vehicular networks; they find that CR networks outperform VANETs when multiple types of packets are transmitted in a vehicle-to-vehicle environment. In [20], Taherkani and Pierre propose a multiobjective algorithm for congestion control in VANETs; their proposal is evaluated under highway and urban scenarios to find that it outperforms schemes like CSMA/CA, D-FPAV (Distributed-Fair Power Adjustment for Vehicular Environments), and CABS (Context Awareness Beacon Scheduling). Finally, the authors in [21] evaluate the influence of packet error models on VANET simulations.…”

Section: Broadcast Models For the Control Channelmentioning

confidence: 99%

A Simulation‐Based Analysis of the Loss Process of Broadcast Packets in WAVE Vehicular Networks

González

Ramos

2018

The IEEE 802.11p standard operates with the WAVE (Wireless Access in Vehicular Environments) system in vehicular ad hoc networks (VANETs). The broadcast process is used to send messages for safety and non-safety applications. A previous work on broadcast packets over the control channel proposes an analytical model to study the loss process. Even if such work does not consider all of the phenomena affecting the operation of vehicular networks, we can obtain a very good approximation of the performance that VANETs may exhibit. Regardless of its importance, this subject has been barely studied. Moreover, there is in the literature only a couple of contributions on this subject, being both analytical models. Therefore, we present in this paper an analysis of the loss process of broadcast packets on the control channel of VANETs over different scenarios. First, we consider a typical two-way scenario and then we analyze a scenario with intersections, both for different vehicle densities. We conduct a campaign of extensive simulations with the NS-3 simulator to study the average loss rate of broadcast packets, and then we compare our results with an analytical model proposed by Campolo et al. We prove the relationship among the contention window, the packet size, and the number of vehicles with the loss rate, including losses caused by noise, collisions, hidden terminal, and channel switching. Thus, we analyze the loss process validating the results obtained by Campolo et al. We find that there are additional factors affecting the loss rate, which cannot be captured with the analytical model. One key finding in this work is that the loss rate due to channel switching differs between both approaches. Also, we find bounds on the use of the control channel, with the loss rate and the traffic load in the network as parameters.