5 research outputs found

    Reinforcement Learning-Based Data Rate Congestion Control for Vehicular Ad-Hoc Networks

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    Vehicular Ad-Hoc Network(VANET) is an emerging wireless technology vital to the Intelligent Transportation System(ITS) for vehicle-to-vehicle and vehicle-to-infrastructure communication. An ITS is an advanced solution that aims to deliver innovative services pertaining to various transportation modes and traffic management. Its objective is to enhance user awareness, promote safety, and enable more efficient and coordinated utilization of transport networks. ITS aims to mitigate traffic problems and improve the safety of transport by preventing unexpected events. When the vehicle density, i.e., the number of vehicles communicating in a wireless channel, increases, the channel faces congestion resulting in unreliable safety applications. Various decentralized congestion control algorithms have been proposed to effectively decrease channel congestion by controlling transmission parameters such as message rate, transmission power, and data rate. This thesis proposes a data rate-based congestion control technique using the Q-Learning algorithm to maintain the channel load below the target threshold. The congestion problem is formulated as an MDP and solved using a Q-learning algorithm. Q-learning is a model-free Reinforcement Learning algorithm that learns the values of an action within a specific state without relying on an explicit model of the environment. Reinforcement Learning has a set of states and actions and will find the best action for each state. The target is to train the vehicle to select the most appropriate data rate to send out a Basic Safety Message(BSM) by maintaining the channel load below the target threshold value. We use the Q-Learning algorithm with data obtained from a simulated dynamic traffic environment. We define a reward function combining CBR and data rate to maintain the channel load below the target threshold with the least data rate possible. Simulation results show that the proposed algorithm performs better over other techniques such as Transmit Data rate Control(TDRC), Data Rate based Decentralized Congestion Control(DR-DCC) and Data Rate Control Algorithm (DRCA) in low and medium loads and better over TDRC and DR-DCC in heavy load in terms of the Channel Busy Ratio (CBR), packet loss and Beacon Error Rate (BER)

    Design of an adaptive congestion control protocol for reliable vehicle safety communication

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    Transmission Data Rate Control based Mechanism for Congestion Control in Vehicular Ad Hoc Networks (VANET)

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    Vehicular Ad Hoc Networks (VANET) supporting Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (v2I) communication can increase the efficiency and safety of the road transportation systems. VANET typically uses wireless communication technology and in scenarios with high vehicle densities, the communication channel faces congestion, negatively impacting the reliability of the safety applications. To prevent this, the European Telecommunication Standards Institute (ETSI) has proposed the Decentralized Congestion Control (DCC) methodology to effectively control the channel load, by controlling various message transmission parameters like message rate, data rate, and transmission power. Currently, most research works focus on the transmission power to control congestion, while the other approaches such as data rate and message rate control are less common. In this research, a data rate control algorithm has been proposed to control the network congestion based on the Channel Busy Ratio (CBR). For the simulations, real-world scenarios generated throughSUMO are considered. After comparing the results with other data rate control algorithms, the proposed approach is anticipated to perform better in the scenarios where the CBR is dynamic and high

    Mobile Ad-Hoc Networks

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    Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

    A collision-based beacon rate adaptation scheme(CBA) for VANETs

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