Lu, Yang, Fang, Jinghan, and Xiang, Wei (2025) An Adaptive Susceptible-Infected-Recovered Based Gossip Protocol via High-Order Adjoint Control for Urban Intersection in Smart Cities. IEEE Internet of Things Journal, 12 (24). 53427.

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Abstract

The Susceptible-Infected-Recovered paradigm (SIR) coupled with decentralized gossip remains central to information flow and misinformation mitigation in heterogeneous urban networks, yet static parameters (β, γ, τ) and limited adaptivity hinder responsiveness under rapidly varying conditions. We propose the stochastic trust-enhanced calibration algorithm (STCA), which unifies dynamic trust updates with adaptive gossip control under a high-order Hamilton-Jacobi-Bellman (HJB) stochastic optimization framework. At its core, the STCA performs iterative calibration of (β, γ, τ) via gradient descent augmented by fractal-inspired performance metrics and recursive coupling operators, yielding robust stability guarantees and real-time adaptation to mobility and load fluctuations. Experiments demonstrate a 50 % reduction in detection time (15 s vs. 30 s), an isolation-efficiency gain of approximately 19 % (0:95 vs. 0:80), and a 50 % increase in communication throughput (1200 units vs. 800 units). These results indicate that jointly enhancing trust dynamics, stochastic control, and adaptive gossip via STCA constitutes a scalable technological advancement for smart-city information dissemination, delivering certificate-oriented stability and performance suitable for next-generation (6G+) deployments.

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