Adaptive Beacon Broadcast in Opportunistic Routing for VANETs

Broadcast of beacon messages including geographic coordinates, node speeds, and directions are among the most commonly used methods in routing protocols of VANETs to obtain neighboring positions. Broadcast of periodic beacon messages in fixed time intervals will reduce network performance due to increased channel load and contention. In this paper, an adaptive update strategy for sending beacon messages according to the VANETs’ characteristics (position, speed, and direction) and the nature of broadcast wireless channel in an opportunistic routing strategy is studied. It is based on two rules: 1) an estimation of the lifetime of the links between vehicles’ beacon messages are sent after the expiration of the estimated time to inform their local topology and 2) if the forwarding set of consecutively received data packets is changed, a beacon message is sent to maintain the accuracy of the topology. The simulation results show that the proposed strategy significantly reduces the cost of routing and improves network performance in terms of packet-delivery ratios, average end-to-end delay, and routing overhead

Packet Size-Aware Broadcasting in VANETs With Fuzzy Logic and RL-Based Parameter Adaptation

Most existing multi-hop broadcast protocols for vehicular ad hoc networks (VANETs) do not consider the problem of how to adapt transmission parameters according to the network environment. Besides the propagation environment which determines the channel bit error rate, packet payload size has a significant effect on the packet loss rate. In this paper, we first discuss the effect of packet size on the packet reception ratio, and then propose a broadcast protocol which is able to specify the best relay node by taking into account the data payload size. The proposed protocol employs a fuzzy logic-based algorithm to jointly consider multiple metrics (link quality, intervehicle distance, and vehicle mobility) and uses a redundancy transmission approach to ensure high reliability. Since the fuzzy membership functions are tuned by using reinforcement learning, the protocol can adapt to various network scenarios. We use both real-world experiments and computer simulations to evaluate the proposed protocol

マルチチャネルスキームと階層的リソーススケジューリングを備えた車両のインターネットのための効率的なブロックチェーンに向けて

電気通信大学202