Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning
Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Information (peak AoI, also abbreviated PAoI) to stay below a hard per-slot deadline, not merely an average bound. Existing approaches meet this requirement only under restrictive assumptions: stochastic channels for Whittle-index AoI, simulator rollouts for deep reinforcement learning, or sublinear cumulative violation for long-term constrained online convex optimization. Under adversarial coefficients, OCO-PAoI-Hard guarantees zero per-slot violation of the modeled AoI state under one-step viability and O(sqrt(T)) regret against any static saf...
| Authors | Wentao Zhang, Wentao Mo |
|---|---|
| Primary category | cs.LG |
| Published | 30 July 2026 |
| Last updated at source | 3 August 2026 |
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