High-frequency millimeter-wave (mmWave) and Terahertz (THz) communications are promising for 6G Internet of Vehicles (IoV) services but remain vulnerable to dynamic vehicular mobility, bursty heterogeneous traffic, and heavy-tailed physical blockage. Conventional routing approaches often rely on memoryless channel models, non-differentiable soft-computing heuristics, or centralized optimization that may not adequately capture blockage persistence and tail-latency risks. This paper presents FARABI (Fuzzy-Assisted Routing for Adaptive Blockage-Resilient 6G IoV), a cross-layer Software-Defined Networking (SDN) routing framework that integrates a three-state semi-Markov blockage model, multi-class Markov-Modulated Poisson Process (MMPP) traffic, a seven-dimensional differentiable fuzzy inference system, and Conditional Value-at-Risk (CVaR)-based risk-aware routing optimization. The framework tracks blockage age to estimate residual interruption duration and incorporates queueing, link reliability, route sustainability, and traffic-class requirements into an online hierarchical primal-dual optimization process. Extensive simulation-based evaluation under dynamic blockage, mobility, and bursty traffic conditions shows that the FARABI control-plane execution time increases from 0.5 ms to 1.85 ms as the decision space grows from 450 to 18,000 variables, corresponding to up to 42.08× lower computational time than a centralized interior-point solver. Under increasing obstacle density, FARABI sustains an effective service rate from 4.62 to 1.88 Gbps, while conditional outage reaches 54.2% at a blockage age of 180 ms. Under severe blockage dynamics, 58.4% of packets are delivered within 1.6 ms, 94.1% within the 3.2-ms tail-latency target, and the median end-to-end delay is 1.48 ms. Across burstiness levels from 1.5 to 5, safety, cooperative-perception, and infotainment packet-loss rates remain within 0.002–0.098%, 0.045–0.98%, and 0.42–10.15%, respectively. These results indicate that FARABI can improve the robustness of SDN-based 6G IoV routing against stochastic blockage and bursty traffic while maintaining bounded computational and QoS performance.
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Shahrzad Sedaghat (2026) studied this question.
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