# An Intelligent Fuzzy-Based Routing Protocol for Vehicular Opportunistic Networks
## 1 Introduction  
Opportunistic networks (OppNets) represent a subclass of Delay-Tolerant Networks (DTNs) where data transfer occurs through intermittent connections between nodes, without requiring a fully connected path [1]. Nodes in these networks, typically mobile entities such as vehicles or smartphones, leverage store-carry-forward paradigms to transfer messages. OppNets are particularly suited to environments with high node mobility and sparse connectivity, such as vehicular networks [2], disaster recovery scenarios [3], and rural communication systems [4]. However, the inherent lack of consistent end-to-end paths introduces significant challenges in routing, as traditional protocols cannot ensure reliable and efficient delivery in such environments [5].  
The primary challenges in routing for OppNets include managing limited resources such as buffer space, energy, bandwidth, and privacy while maximizing delivery probability and minimizing delays [6, 7]. Frequent disconnections and varying node mobilitypatterns further complicate the task of identifying optimal forwarding strategies. In vehicular OppNets, these challenges are amplified by rapid topology changes, variable traffic conditions, and the unpredictability of vehicle mobility [8]. Existing protocols, such as Epidemic [9] and MaxProp [10], while effective in some scenarios, often suffer from excessive overhead or poor scalability under high message generation rate conditions [11].  
To address these challenges, this study proposes a novel routing protocol for OppNets, named the Fuzzy Control Routing Protocol (FCRP), which utilizes fuzzy logic to make decisions for message forwarding. The proposed protocol incorporates buffer occupancy, the angle to the destination, and the number of unique connections of the target nodes as input parameters to evaluate the forwarding potential of nodes. These parameters are crucial for capturing the dynamic and resource-constrained nature of vehicular OppNets. By employing a fuzzy-based approach, the protocol adapts to the inherent uncertainties in node behavior and network conditions, enabling more efficient routing decisions.  
Fuzzy logic is particularly well-suited for this scenario due to its ability to model imprecise and uncertain inputs. Unlike traditional deterministic algorithms, fuzzy logic systems can evaluate complex relationships between input parameters and produce nuanced outputs, which are critical in the dynamic and unpredictable environment of OppNets. This flexibility allows the proposed protocol to balance competing objectives such as delivery probability and resource usage effectively. Through extensive simulations, we demonstrate that the FCRP outperforms traditional approaches like Epidemic across all metrics, whereas with MaxProp it achieves comparable delivery probability with significantly less overhead, validating its efficacy in addressing the challenges of routing in vehicular OppNets.  
The remainder of the paper is organized as follows. Section 2 presents OppNets, routing protocols used in these networks, and a review of recent work conducted in this field. Section 3 describes the system design and implementation details of the FCRP. Section 4 discusses the evaluation results. Section 5 summarizes the findings of the paper and gives directions over future work.