An Adaptive Susceptible-Infected-Recovered-Based Gossip Protocol via High-Order Adjoint Control for Urban Intersection in Smart Cities

Yang Lu, Jinghan Fang, Wei Xiang

Abstract: The susceptible–infected–recovered (SIR) paradigm coupled with decentralized gossip remains central to information flow and misinformation mitigation in heterogeneous urban networks, yet static parameters ( $\beta,\gamma $ , and $\tau $ ) 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 ( $\beta,\gamma $ , and $\tau $ ) 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 $(15\ \text {versus}\ 30{\,}\mathrm {s})$ , an isolation-efficiency gain of approximately 19% $(0.95\ \text {versus}\ 0.80)$ , and a 50% increase in communication throughput $(1200\ \text {units}\ \text {versus}\ 800\ \text {units})$ . 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.

External IDs:dblp:journals/iotj/LuFX25