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With the emerging applications of the Internet of Things (IoT), a congestion control mechanism becomes a critical phenomenon for efficient communication in networks of constrained devices. The Internet Engineering Task Force developed the constrained application protocol (CoAP) as a standard communication protocol that favors lightweight interoperability for accommodating resource‐constrained devices. However, the base CoAP specification congestion control is insensitive to various network conditions. Thus, differentiating the scenario of packet loss due to bit error rate and congestion, and identifying correct round trip time (RTT) of retransmitted message‐acknowledgement is quite essential to adapt the CoAP behavior based on the network status. In this paper, we present a context‐aware congestion control (CACC) approach for lightweight CoAP/user datagram protocol–based IoT traffic. The CACC proposes mechanisms that include retransmission timeout (RTO) estimator, retransmission count–based smoothed round‐trip‐time observation, lower bound RTO restriction approach, and aging concept. The proposed RTO estimators utilize the strong, weak, and failed RTT to identify exact network status and provide adaptive congestion control. The CACC incorporates the variable of retransmission count in request‐response interaction model to mitigate the negative variation in RTT due to the fluctuation in the IoT environment. Moreover, with lower bound RTO restriction approach, the unnecessary spurious retransmissions are avoided, and the aging mechanism limits the validity of the RTO value to improve the efficiency of the proposed scheme. The proposed model is validated against baseline CoAP and CoCoA+ using Contiki OS and the Cooja simulator. The results are impressive under different network topologies.

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The Constrained Application Protocol (CoAP) is a lightweight web transfer protocol designed based on the REST architecture standardized by the Internet Engineering Task Force (IETF) to meet and accommodate the requirements of the constrained Internet of Things (IoT) environments. Managing congestion control in a resource-constrained lossy network with a high bit error rate is a significantly challenging task that needs to be addressed. The primary congestion control mechanism defined by CoAP specification leverages on basic binary exponential backoff and often fails to utilize the network dynamics to the best of its traffic conditions. As a result, CoCoA has been introduced for better IoT resource utilization. In addition, CoCoA retransmission timeout (RTO) for network dynamics is based on constant coefficient values. The resource-constrained nature of IoT networks poses new design challenges for congestion control mechanisms. In this paper, we propose a new particle swarm optimization (PSO)-based congestion control approach called psoCoCoA as a variation of CoCoA. The psoCoCoA applies random and optimal parameter-driven simulation to optimize default CoAP parameters and update the fitness and velocity positions to adapt to the traffic conditions. This process is performed for different traffic scenarios by varying the retransmission and max-age values by using the optimization-based algorithm. We carried out extensive simulations to validate the congestion control performance for CoAP with Observe, CoCoA, and psoCoCoA with different network topologies. The results indicate that psoCoCA outperforms or very similar to CoCoA and achieves better performance compared to CoAP with Observe under different network scenarios. | INTRODUCTIONThe ever-growing Internet of Things (IoT) is paving the way for the global network infrastructure, and the number of devices interconnected to the IoT is proliferating, which in turn leads to several diverse smart applications and services. 1 In view of the tremendous potential of the IoT, it is predicted that more than 50 billion Internet-capable smart things will be connected over the Internet shortly, and this will tend to revolutionize the global world. 2 The IoT connects numerous heterogeneous devices by applying a wide range of technologies that include communication, networking, and information processing and ensures inter-operability among global Internet services by integrating smart objects into the existing network and information systems. [3][4][5]