A Survey on Nature-Inspired Control Methods for IoT and Communication Networks

Modern Internet of Things (IoT) and communication networks operate under dynamic, large-scale, and resource-constrained conditions where conventional control can falter. This survey synthesizes 108 peer-reviewed (including preprints) studies (2007–2025) on nature-inspired control mapped to the TCP/IP stack across the classes of network functions. The survey introduces a three-axis taxonomy (TCP/IP layer × biological metaphor × function) and a unified KPI scheme with a normalization formula to compare heterogeneous reports. Aggregated evidence indicates typical gains of 20–50% energy reduction, 25–40% delivery-ratio improvement, 10–35% latency reduction, and > 0.95 F1 for immune-inspired intrusion detection, when compared to canonical baselines. This survey further makes explicit how few studies validate on real hardware or under adversarial conditions. Moreover, this survey analyzes real-time constraints, hyperparameter sensitivity, and integration pathways with 6LoWPAN/RPL, TSCH/6TiSCH, MQTT, and CoAP, outlining steps toward deployable, explainable, and deterministic nature-inspired control.