Aug 2026· Journal of Internet Services and Applications· 0 citations· 32 references
TL;DR
The proposed SPN model enables system architects to compare routing configurations, identify performance bottlenecks, and size infrastructure components without requiring physical deployment, and enables the identification of communication bottlenecks without requiring physical deployment.
Abstract
Vehicular ad hoc networks (VANETs) have emerged as a critical enabler of intelligent transportation systems, particularly when integrated with 5G infrastructure to achieve high-throughput, low-latency vehicle-to-everything (V2X) communication. Nevertheless, optimizing message routing in such environments remains a significant challenge, as the operational complexity and prohibitive cost of large-scale physical deployments severely limit empirical evaluation of alternative transmission strategies. This paper presents a stochastic Petri nets (SPNs) model for evaluating routing configurations in 5G-enabled vehicular ad hoc networks (5G-VANETs). The proposed model evaluates mean response time, drop probability, utilization, and throughput, enabling the identification of communication bottlenecks without requiring physical deployment. By abstracting the system's stochastic behavior through SPN formalism, the model supports both steady-state analysis and sensitivity evaluation under varying traffic workloads. Results demonstrate that Route 1, with direct RSU connection, achieves the lowest mean response time and highest throughput, while Route 3, which relays messages through a rear vehicle and an auxiliary RSU, yields the lowest drop probability. A sensitivity analysis based on Design of Experiments reveals that cloud capacity and cloud service time are the dominant factors affecting mean response time. The SPN model thus enables system architects to compare routing configurations, identify performance bottlenecks, and size infrastructure components without requiring physical deployment.
An extensive evaluation of Software-Defined Networking integrated with two traffic engineering technologies, Multi-Protocol Label Switching (MPLS) and Segment Routing (SR), applied to the AODV and OLSR routing protocols demonstrates that SR with distance-based IS-IS metrics achieves the highest Packet Delivery Ratio (PDR) and lowest delay.
Ronild Hako, E. Spaho, A. Annuk· Network· 0 citations
Wireless Mesh Networks (WMNs) are a key enabling technology for dynamic, infrastructure-limited IoT environments. The routing protocol is the central design choice in any WMN deployment because throughput, end-to-end delay, energy consumption and delivery reliability are directly affected by it. A systematic, simulation-based evaluation of two widely studied WMN routing protocols is presented: the reactive Ad hoc On-Demand Distance Vector (AODV, RFC 3561) protocol and the proactive Destination-Sequenced Distance-Vector (DSDV) protocol. Simulations were conducted in OMNeT++ 6.3 with the INET 4.5 framework across five network densities $(N \in\{10,20,30,40,50\}$ nodes) in a $1000 ~\mathrm{m} \times 1000 ~\mathrm{m}$ IEEE 802.11g area with a many-to-one UDP traffic pattern representative of IoT data collection. A density-dependent crossover was revealed at approximately $N=20$: lower delay was achieved by DSDV in sparse networks, whereas higher throughput, higher delivery reliability and lower energy consumption were achieved by AODV at higher densities. At $N=50, \approx 35 \%$ higher throughput, zero routing failures and $\approx 8 \%$ lower energy consumption are delivered by AODV. It is indicated by the MAC-layer contention behavior that DSDV's high-density degradation is mainly driven by IEEE 802.11 channel saturation rather than by routing-algorithm deficiencies. Deployment guidelines derived from these findings are provided.
Alá F. Khalifeh, Abdulla Ababneh, Iacovos I. Ioannou· IEEE Jordan Conference on Ap...· 0 citations
This research bridges the gap between theoretical queuing models and practical routing strategies, contributing to the development of more efficient routing protocols for MANETs and demonstrates significant improvements in delay, throughput, routing overhead and node lifetime under realistic traffic conditions.
Multipath routing is a key strategy for meeting the Quality of Service (QoS) requirements of video applications in the Internet of Things (IoT). However, the objective functions used in heuristic-based multipath selection mechanisms are often defined through mathematical models or network performance estimators and typically validated only in simulators, which may fail to capture the full complexity of real-world wireless environments. This paper presents the design and validation of a physical testbed composed of low-cost, single-board computers for wireless multipath video transmission. Beyond evaluating hardware resource usage (CPU, memory, and thermal load), we conduct a comprehensive cross-layer case study to assess the predictive reliability of the FITPATH and QSOpt routing heuristics. Transitioning from traditional QoS metrics to perception-based Quality of Experience (QoE), we evaluate the Structural Similarity Index (SSIM) across video sequences with varying degrees of motion and network load. Our findings reveal that while simulators capture general trends, high-motion video significantly degrades latency, suggesting the occurrence of intermediate queue bottlenecks. Furthermore, our video quality gap analysis demonstrates that while FITPATH provides highly accurate relative path rankings, both heuristics struggle to predict absolute performance drops caused by real-world interference. Ultimately, this work underscores the necessity of physical testbed validation for interference-aware objective functions in IoT multimedia networks.
G. A. Barbosa, F. Bhering, C. Albuquerque et al.· Annals of Telecommunications· 0 citations
The rapid advancements of next-generation vehicular networks require intelligent, low-latency, and efficient resource management to support heterogeneous services. In this work, we propose a Traffic-aware Dynamic Resource Allocation (TADRA) architecture for UAV-assisted vehicular O-RAN to address the challenges of dynamic traffic conditions, infrastructure failures, and stringent quality of service (QoS) requirements. Due to the dynamic mobility and flexible deployment characteristics, UAV Open Radio Units (O-RUs) in the TADRA architecture support the terrestrial infrastructure under overload or failure conditions, dynamically extending coverage, balancing traffic loads, and restoring service to maintain uninterrupted QoS across diverse and heterogeneous traffic demands. Unlike existing static or single-layer solutions, our proposed TADRA integrates RAN Intelligent Controllers (RICs) with a Hierarchical Traffic-Aware Multi-Agent Twin-Delayed (TMT) algorithm to optimize the allocation of computation and radio resources. This joint optimization problem is NP-hard, highly dynamic, and coupled across agents, making TMT a tractable and adaptive alternative. This hierarchical framework performs traffic prioritization at the upper (application) layer and resource allocation at the lower (MAC) layer, facilitating adaptive decision-making under diverse vehicular traffic patterns. Numerical results demonstrate that our solution provides substantial gains over MATD3, MADDPG, and GA, achieving 17% lower latency, 10% higher throughput, 14% lower energy consumption, and 6.5% higher reliability.
Hayla Nahom Abishu, Ahmed Badawy, Amr Mohamed et al.· IEEE Transactions on Network...· 0 citations
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