falcon-coap: end-to-end fuzzy congestion detection and control for the constrained application protocol in iot

Efficient congestion control is a fundamental requirement to ensure quality of service (qos) in computer networks, particularly in low-power and lossy networks (llns). the constrained application protocol (coap), widely adopted in iot environments, lacks built-in mechanisms for effective congestion control due to its reliance on udp. its basic congestion control, based on fixed timers and retransmissions, often results in inefficient operation, unnecessary retransmissions, and delayed responses to packet losses. this paper introduces falcon-coap, a novel fuzzy based congestion control scheme equipped with an loss detection module. the proposed system dynamically distinguishes between congestion-induced and non-congestive losses, enabling adaptive adjustment of retransmission timeout (rto) and transmission rate. simulation results obtained in cooja/contiki demonstrate that falcon-coap outperforms existing state-of-the-art methods in terms of throughput, end-to-end delay, and energy efficiency, offering a more responsive and reliable congestion control solution for iot networks.