Jul 2026· Turkish Journal of Electrical Engineering and Computer Sciences· 0 citations
Abstract
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.
The results demonstrate that the proposed PP-SAPF is suitable for real-time deployment in intelligent transportation systems (ITS) and autonomous vehicles where low latency, reliable connectivity, and adaptive resource management is significant.
Irshad Khan, Neetha Papanna Umalakshmi, Somshekhar Durgaiah et al.· Bulletin of Electrical Engin...· 0 citations
Simulation results validate the convergence and efficiency of the proposed algorithm while highlighting the impact of critical parameters on system performance, providing valuable insights for resource allocation in aggregated VLC–RF vehicular networks.
Huanhuan Qin, Xizheng Ke· Italian National Conference...· 0 citations
This paper proposes a hierarchical computation framework that flexibly supports task execution across local vehicles, neighboring vehicles, RSUs, and cloud resources, and designs an efficient task migration and resource scheduling strategy that improves overall system performance under dynamic network conditions.
Liqun Yang· Journal of Grid Computing· 0 citations
Vehicular Internet of Things (V-IoT) networks require reliable scheduling for safety-critical communication, cooperative awareness, and cooperative perception under dynamic mobility and limited roadside infrastructure. This paper proposes MoReSP, a Mobility- and Reliability-aware Scheduling Policy for roadside unit (RSU)-assisted V-IoT networks. MoReSP uses mobility-regime inference, structured action scoring, safety projection, and episodic parameter adaptation to select among deny, grant, preempt, coexist, and handoff actions. Its multiobjective formulation jointly minimizes average delay, communication energy consumption, admission-adjusted reliability loss, a penalty for cooperative perception message (CPM) delivery/freshness, and RSU-load imbalance. The framework is evaluated under vehicle-load variation, Nagel–Schreckenberg (NaSch) density variation, and RSU-capacity scaling using admission-adjusted metrics that penalize excessive blocking and interruption. MoReSP is compared with five literature-grounded benchmark families: Age of Correlated Information (AoCI)-Heuristic, RSU-Coop, Handoff-Aware, vehicle-to-everything (V2X)-Priority, and Adaptive Learning-based Task Offloading multi-armed bandit (ALTO-MAB). Simulation results show that MoReSP achieves the lowest admission-adjusted system cost across all evaluated scenarios. At nominal RSU capacity, MoReSP reduces the system cost by 43.6% compared with the best baseline. Under high vehicle load, it reduces the cost by 54.4% at arrival scale 2.0 and maintains effective packet and CPM delivery ratios of 0.849 and 0.828, respectively. These results demonstrate that MoReSP provides a reliable and balanced scheduling solution for dynamic V-IoT environments.
Muhammad Faisal Siddiqui, Adeel Iqbal· Mathematics· 0 citations