Survey on Congestion Detection and Control in Connected Vehicles

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

A comprehensive survey on congestion control techniques and the research challenges on VANET

The nature of vehicular mobility and high speed of vehicular ad hoc network (VANET) with dynamic change in the network topology let the vehicular remain as one of the most challenging problems in vehicular-to-vehicular (V2V) communications. Information dissemination is the major problem in VANET with a fixed bandwidth which is causing congestion on the resources, such as channels and affects the performance of the important application, especially when the emergency or secure transmission of messages is exchanged between the vehicles-to-vehicles communication. To mitigate these problems and introduce a safe vehicular environment in urban and highway, congestion detection and control has been considered and with various strategies and techniques which is take the attention of researchers in VANET. In our survey we mentioned recent techniques and approaches which is used in congestion detection and control and applied different matrices and parameters which is used to evaluate these approaches. In addition, the study also explained the limitation and problems that face the current congestion detection and control schemes, finally we present various solution approach and future expectations in vehicular communication

Congestion avoidance through fog computing in internet of vehicles

Recently, internet of vehicles (IoVs) is captivating a lot of interest due to a wide range of applications in various domains. These applications rely on up-to-date information of vehicles for provisioning various services. However, frequent message transmissions by a sheer number of vehicles may not only engulf a centralized server but may also cause a severe congestion which is not suitable for ongoing services specially in emergency situations. The aim of this study is to reduce congestion and messaging overhead. This paper presents a fog-assisted congestion avoidance scheme for IoV named energy efficient message dissemination (E2MD). Unlike most of the existing schemes, E2MD capitalizes the merits of fog computing to minimize communication cost and manage services. Each vehicle is required to update their status to a fog server frequently, either directly or through intermediate nodes. In case of an emergency, the fog server will timely inform upcoming traffic to slow down, dispatch rescue teams to provide necessary services, and coordinate patrolling missions to clear the road. Moreover, failure detection and recovery mechanisms are also presented to ensure availability of the fog server. The performance of the proposed scheme is validated through NS 2.35 simulations. Simulation results confirm the performance reign of E2MD compared to contemporary schemes in terms of latency and communication cost. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature