Agentic Lightweight Consensus for Resilient Monitoring and Control of Modern Data Centers in Smart Cities

Abstract

Modern data centers underpin smart-city services, yet their control loops must reconcile noisy, missing, or deliberately deceptive telemetry before acting autonomously. We present a two-path agentic architecture in which a deterministic fast path fuses sensor reports through a reliability-based fuzzy-preference OWA operator (FPR–OWA) and a persistent consensus-reaching process (CRP), while an optional reactive or LLM supervisor can only propose typed actions that a deterministic verifier must admit. Across 1890 indexed simulation scenarios and seven attack families, no estimator dominates: averaging attains the lowest global error and sensor redundancy explains most of the accuracy variation, whereas FPR–OWA + CRP provides the strongest anomaly-diagnostic signal. We prove that logistic dominance preserves the reliability ordering and add a zone-dynamic temporal-consistency ablation. In the original safety campaign, no unsafe execution was observed in the verifier-gated episodes, and the unified process-local runtime later passed all 24 deterministic fault-injection cases; both are empirical, not formal, guarantees. An illustrative closed-loop pilot adds standard control metrics and reveals delayed recovery under common-mode sensor bias; a CPU benchmark keeps persistent-CRP median latency below 0.30 ms at 100 sensors. The result is a reproducible, bounded blueprint for verified autonomy in datacenter infrastructure; hardware validation, production authentication, and energy measurement remain future work.