Aug 2026· International Journal of Advanced Research in Science, Communication and Technology· 0 citations· 5 references
TL;DR
The proposed framework separates network control from forwarding, maintains a global view of vehicular network state, classifies V2X flows by service criticality, and dynamically selects routes and bandwidth allocations using delay, congestion, handover, and priority constraints.
Abstract
Vehicle-to-Everything (V2X) communication requires low-latency, reliable, and context-aware connectivity across vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian, and vehicle-to-network services. Heterogeneous cellular networks can support these services by combining 5G New Radio, cellular sidelink, roadside units, Wi-Fi or DSRC links, and multi-access edge computing; however, high mobility, variable traffic density, frequent handovers, congestion, and static resource-allocation policies can degrade end-to-end delay and packet delivery. This paper presents a software-defined networking assisted framework for latency-aware resource management in heterogeneous V2X environments. The proposed framework separates network control from forwarding, maintains a global view of vehicular network state, classifies V2X flows by service criticality, and dynamically selects routes and bandwidth allocations using delay, congestion, handover, and priority constraints. A mathematical formulation is developed for minimizing weighted end-to-end latency under link-capacity, minimum-bandwidth, packet-delivery, congestion, and controller-processing constraints. The paper also defines the Latency-Aware SDN Resource Allocation Algorithm for V2X Networks and specifies a reproducible simulation methodology using NS-3/SUMO or OMNeT++/Veins with multiple baselines, confidence intervals, and ablation analysis. Because the source report did not include raw simulation data, the revised results section includes clearly labelled hypothetical numerical plots and reporting values only to demonstrate result formatting and interpretation; these values are not validated empirical findings. The study provides a rigorous foundation for validating SDN-MEC orchestration in next-generation vehicular communication systems
A coordinated communication and computing resource management framework for O-RAN-based V2N communications and demonstrates a balanced trade-off among SLA compliance, computing-resource satisfaction, delay, throughput, and mobility robustness, while also showing that load-aware steering can provide higher aggregate SLA compliance under specific traffic distributions.
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
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
Handover management in LoRaWAN networks is a critical challenge for dynamic IoT applications such as connected vehicles and drones. Existing approaches fail to simultaneously satisfy low latency, active handover with full context transfer, and scalability without modifying end devices. This paper proposes LoRa-PDMM, a hybrid architecture combining local Distribution Servers for fast intra-zone handover and a Central Server for inter-zone coordination, without any modification to existing end devices. Evaluation uses discrete-event simulation (Python/SimPy) with explicit LoRaWAN constraints including 1% duty cycle, Class A RX1/RX2 windows, ALOHA-based channel access with capture effect, and configurable context size, over scenarios from 10 to 100 mobile nodes with Random Waypoint and Gauss-Markov mobility. LoRa-PDMM reduces server-side handover latency by 54.7% and total latency by 23.2% over a centralized active handover baseline, with packet delivery ratio between 86.1% and 98.6% under nominal conditions. The latency reduction targets the server-side processing component, which is the architectural variable LoRa-PDMM directly controls; the Class A downlink window wait is a LoRaWAN protocol constraint common to all approaches.
Djièta Ouindé Abdoul Fatas Bamogo, Bernard Armel Sanou, Pasteur Poda· International Conference on...· 0 citations
Vehicular networks support intelligent transportation through vehicle-to-roadside Units (V2R) and vehicle-to-vehicle (V2V) communication but face challenges from dynamic topologies, limited RSU coverage, and bandwidth scarcity, which impact service delivery and revenue. RDA-ITU addresses these challenges by integrating V2R and V2V paradigms to maximize RSU revenue, enhance service availability, and improve system efficiency. It dynamically allocates services based on real-time network conditions and vehicle mobility, leveraging V2V relays to optimize both RSU-direct and cooperative communication. Through extensive simulations, RDA-ITU significantly outperforms four baselines: RBSM, VVMM-U, VVMM-LW, and VVMM-MA. It achieves 81.1% higher total revenue, 154.8% more completed requests, and 103.6% higher average data delivery. Specifically, versus RBSM, gains reach 77.6% in revenue, 228.0% in TCR, and 242.4% in TDD; against VVMM-U: 32.6%, 43.9%, and 47.9%; versus VVMM-LW: 153.7%, 74.5%, and 284.1%; and versus VVMM-MA: 25.7%, 30.2%, and 53.7%, respectively. These improvements stem from RDA-ITU’s core mechanisms: revenue-optimized candidate sorting, dynamic V2V relay pairing, and adaptive bandwidth allocation. Prioritizing high-revenue services and facilitating efficient cooperative offloading, RDA-ITU ensures strong performance in dense mobile environments, thus promoting revenue-aware vehicular edge computing.
A. Saluja, Satyabrata Das, S. K. Nayak et al.· Turkish Journal of Electrica...· 0 citations
The deployment of Ultra-Dense Networks (UDNs) in 5G systems is to meet the growing demand for high data rates and massive connectivity. However, the dense deployment of small cells increases handover frequency, leading to challenges such as handover failures (HOF), unnecessary handovers, and the ping-pong effect, leading to degradeuser Quality of Service (QoS). This paper proposes a velocity-aware adaptive handover control approach for efficient mobility management in 5G ultra-dense networks. The proposed approach dynamically adjusts Handover Control Parameters (HCPs) called Time-to-Trigger (TTT) and Handover Margin (HOM) on the real-time velocity of User Equipment (UE) and signal conditions. The system is modeled as a two-tier heterogeneous network consisting of a macrocell overlaid with multiple small cells, and performance is evaluated using the Cost 231-Hata propagation model. The findings demonstrate that the proposed algorithm significantly reduces the total number of handovers, mitigates the ping-pong effect, and lowers handover failure rates compared to conventional static schemes. The results confirm that velocity-aware adaptive control enhances network reliability, reduces signaling overhead, and improves overall mobility performance in 5G ultra-dense environments.
Halah Hassen Aldumaini, Hanadi Esmeail Yahya, Oloof Ameen Mohmmed et al.· 2026 6th International Confe...· 0 citations