## 3 Literature Review
The objective is to incorporate fuzzy logic decision-making in selecting the next-hop nodes by considering multiple metrics related to the vehicle's position, direction, link quality, and available bandwidth. However, FL-DCR routing does not consider the effect of adaptive beaconing. Conversely, [PERSON] et al. [42] also proposed an adaptive beacon strategy for opportunistic routing in VANET. The scheme is based on two rules; the first rule is related to estimating the link establishment time between two nodes, and the second rule is to send an update beacon to neighbors if the consecutively received packet-forwarding set is changed. The aim is to reduce the beacon overhead and maintain the accuracy of the neighbor nodes' toplogy. Moreover, [PERSON] et al. [43] proposed a new geographic routing technique to address the communication problems in sparse MANETs. The technique uses geographic location and two-hop neighbor information to create a forwarding-node-selection policy that determines optimal relay candidates that move towards destination nodes in a network. To that aim, the proposed geographic routing strategy has the advantage of reducing routing overhead and end-to-end delay in ad hoc situations. In the contrary, [PERSON] et al. [44] introduced the MObility pattern-free Dynamic and Effective Location update (MODEL) protocol to maintain the trade-off between beacon rate overhead and routing precision in MANET. It employs the fuzzy method to allow for the least amount of inaccuracy in predicting the position rather than in nearby nodes. The Load Balanced-Dynamic Beaconing Greedy Perimeter Stateless Routing (LB-DB-GPSR) is verified using the NS-2 simulator. Furthermore, adaptive GPSR (AGPSR) is introduced in [45] to enhance greedy forwarding and routing choice. The routing model is divided into three phases--initialization, neighbor discovery, and weight value computations--and next-hop selection. The weight value is related with a variety of network characteristics such as node density, node speed, \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Research** & **Year** & **Routing** & **Simulator** & **Network** & **Objective** \\ \hline Ref. [49] & 2022 & \begin{tabular}{c} ABNT \\ (Adaptive Beaconing) \\ \end{tabular} & NS-3 & \begin{tabular}{c} FANET \\ (Adaptive Beaconing) \\ \end{tabular} & \begin{tabular}{c} To establish an adaptive beacon to \\ control the transmission in \\ UAV networks. \\ \end{tabular} \\ \hline Ref. [50] & 2023 & \begin{tabular}{c} UP-GPSR \\ (Fixed Beaconing) \\ \end{tabular} & NS-3 & \begin{tabular}{c} FANET \\ (i.e., optimize greedy forwarding) \\ \end{tabular} \\ \hline Proposed Work & 2023 & \
\begin{tabular}{c} AFB-GPSR \\ (Adaptive Beaconing) \\ Fuzzy-based \\ \end{tabular} & OMNeT & MANET &
\begin{tabular}{c} To update optimal beacon interval \\ to increase network reliability and \\ reduce routing overhead \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._transmission range, network size, congestion level, and movement direction. The Beacon Update Interval (BUI) is determined at the source node and is connected to relative velocity in this study. When the relative velocity is very high, the BUI will be very brief, and the beacon packet will be required frequently. If the relative velocity is very low (i.e., less than 1) and the BUI value is close to the default beacon interval, no additional beacon messages are needed from the neighbor. [PERSON] et al. [46] presented fuzzy-logic-based multi-hop directional location routing (FLMDLR) on VANET networks. FLMDLR determines the optimum next hops using fuzzy logic to construct a stable route from the source node to the destination node. This FLMDLR is investigated using NS-2 and compared to conventional D-LAR and LAR methods. On the other hand, the authors of [47] presented Location-Prediction-with-Adaptive-Beaconing-GPSR (LDAB-GPSR) to improve the mechanism of the GPSR protocol by focusing on optimizing the packet-delivery ratio and reducing the average control overhead.