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. This paper introduces FALCON-COAP, a novel fuzzy-based congestion control scheme equipped with a loss detection module. The proposed system dynamically distinguishes between congestion losses and non-congestion 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.

Keywords:

Internet of Things , Congestion Control , CoAP , Fuzzy Loss Detection