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This paper introduces NANOEDGEGUARD, a kernel-plane closed-loop controller designed to enhance the reliability of healthcare IoT services by managing traffic intensity at the edge. The system employs a multi-tier rate policy that allows for rapid response to traffic bursts, significantly reducing the round-trip time (RTT) for critical alarms by 13.3% compared to traditional user-space firewalls while also cutting excess admitted burst traffic by 46%. These findings highlight the potential for adaptive, auditable traffic control mechanisms to bolster the resilience of healthcare IoT systems in time-sensitive scenarios.
Adaptive kernel-plane traffic control can cut alarm response times by over 13% while slashing burst traffic by nearly half, transforming healthcare IoT reliability.
Healthcare IoT services increasingly rely on edge gateways to relay routine telemetry and deliver rare but timecritical alarms. Even short traffic bursts can inflate worstcase delay and interfere with urgent messages. We present NANOEDGEGUARD, a kernel-plane closed-loop controller that observes per-source traffic intensity at the edge and enforces an auditable, multi-tier rate policy using in-kernel traffic-control hooks. Unlike static firewall rules or user-space control loops, our design prioritizes fast actuation and explicit recovery through hysteresis, and it records policy transitions for auditability. Using a Raspberry Pi gateway hosting an MQTT broker and two ESP32 endpoints generating vitals, alarms, and a timed burst, we show that adaptive kernel-plane rate control reduces the 99th-percentile alarm RTT by 13.3% compared to a user-space firewall baseline while maintaining no-enforcement-level RTT, and it reduces excess admitted burst traffic by 46% compared to no enforcement. These early results indicate that adaptive, auditable enforcement at the gateway can improve resilience for healthcare IoT, and it can be extended toward on-demand policy deployment in future edge intelligence.