A Survey on Congestion Control Protocols for CoAP

The Internet of things (IoT) comprises things interconnected through the internet with unique identities. Congestion management is one of the most challenging tasks in networks. The Constrained Application Protocol (CoAP) is a low-footprint protocol designed for IoT networks and has been defined by IETF. In IoT networks, CoAP nodes have limited network and battery resources. The CoAP standard has an exponential backoff congestion control mechanism. This backoff mechanism may not be adequate for all IoT applications. The characteristics of each IoT application would be different. Further, the events such as unnecessary retransmissions and packet collision caused due to links with high losses and packet transmission errors may lead to network congestion. Various congestion handling algorithms for CoAP have been defined to enrich the performance of IoT applications. Our paper presents a comprehensive survey on the evolution of the congestion control mechanism used in IoT networks. We have classified the protocols into RTO-based, queue-monitoring, and rate-based. We review congestion avoidance protocols for CoAP networks and discuss directions for future work

Design and Evaluation of a Rate-Based Congestion Control Mechanism in CoAP for IoT Applications

CoAP is an application protocol that provides standardised RESTful services for IoT devices. Since COAP messages are encapsulated into UDP datagrams, COAP specification provides: i) optional reliability mechanisms through retransmissions, and ii) simple congestion control mechanisms based on retransmission timeouts. Recent studies have demonstrated that these congestion control schemes may significantly underperform when operating with bursty traffic. To address these limitations, in this paper we propose COAP-R, an alternative solution for regulating the sending rate of CoAP sources, which adopts a rate-based approach for traffic control. Key features of COPA-R are: i) to leverage the tree-based routing structure of IoT networks to estimate the maximum throughput that can be obtained on the bottleneck link of every upward route, and ii) to perform in a distributed manner a max-min fair allocation of available network capacity on the basis of estimated bottleneck bandwidths. The proposed approach is evaluated by means of simulations considering a scenario in which traffic is generated in bursts, for instance as consequence of events detected by sensors. Our simulations demonstrate that the proposed approach ensures a fair allocation of network resources, and leads to a 40% decrease of the data collection delays when compared to COAP