Distance‐based congestion control mechanism for CoAP in IoT

Bansal, Sharu; Kumar, Dilip

doi:10.1049/iet-com.2020.0486

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…Using δ, it estimates the scaling factors δα, δb, and δk, used to estimate RTTcurrent, RTTVARcurrent, and RTOcurrent, respectively. [14] measures RTT using a timestamp and determines the distance between CoAP, the requestor, and the responder using the Euclidean distance formula [31]. The distance between two nodes is determined using the node's coordinates (x, y) (either requestor or responder).…”

Section: Adcocoamentioning

confidence: 99%

“…FASOR has three distinctive featuresan adaptation of the RTO backoff and RTO computation which can be fast or slow. DCC-CoAP [14] efficiently predicts network congestion; it combines the separation of nodes and multiple RTT measurements, reducing CoAP message loss. CoCoA++ [15] uses the delay gradients method to measure network congestion and introduces a new backoff mechanism called probabilistic backoff to deal with congestion.…”

Section: Introductionmentioning

confidence: 99%

“…Figure 5: AdCoCoA working mechanism (source: reference [11]) 3.14 Distance-based congestion control CoAP (DCC-CoAP) DCC-CoAP[14] measures RTT using a timestamp and determines the distance between CoAP, the requestor, and the responder using the Euclidean distance formula[31]. The distance between two nodes is determined using the node's coordinates (x, y) (either requestor or responder).…”

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confidence: 99%

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A Survey on Congestion Control Protocols for CoAP

Deshmukh¹,

Raisinghani²

2022

Int. j. commun. netw. inf. secur.

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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.

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Section: Adcocoamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A Survey on Congestion Control Protocols for CoAP

Deshmukh¹,

Raisinghani²

2022

Int. j. commun. netw. inf. secur.

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“…In basic CoAP, RTO was not dependent on RTT value and later certain solutions came where different RTO values computed considering RTT. However, the paper [13] consider distance between the nodes along with the RTT values for computing RTO. This mechanism would enable to pick nearly optimal value based on the distance ensuring for nearby nodes RTO is small while for distance nodes initial RTO is large.…”

Section: Congestion Mechanismmentioning

confidence: 99%

A Reliable CoAP Protocol for IoT Communication

Bansal

Kumar

2022

Preprint

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The request-response model for constrained devices is achieved via RESTful architecture of Constrained Application Protocol (CoAP) in IoT. An enhanced CoAP is proposed to address the limitations of CoAP to achieve an efficient IoT network. Unlike existing protocols that operate on instantaneous Round-Trip Time (RTT) in IoT, it also makes use of CoAP options, payload, and node distance for defining the network state in a better way. Various new parameters viz. timestamps, priority, message path, device status is introduced and CoAP payload is defined using SenML representation of data. The processing unit at the network level is used for data analysis of the integrated parameters that are timely communicated to this unit from the network nodes. The algorithm with varying data rates is used in homogeneous and mixed traffic to calculate the performance. The significant improvement in terms of delay, priority, congestion, retransmissions ensure reliable communication in the network.

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“…Several works have been presented in Wireless Ad hoc and Sensor Networks for CC in constrained application protocol; recently, CC mechanisms for CoAP are in other studies, [27][28][29][30][31][32][33] and notable contributions on CC for reliable exchanges of CoAP communications include other studies. [20][21][22]24,[34][35][36] The Internet Engineering Task Force (IETF) RFC 7641 18 provides an extension of the CoAP base specification for CC in unreliable CoAP communications as CoAP with Observe, which uses a publish-subscribe mechanism, with the introduction of an upper limit for the permitted rate of outgoing messages.…”

Section: Related Survey Workmentioning

confidence: 99%

An optimization‐based congestion control for constrained application protocol

2021

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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]

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Distance‐based congestion control mechanism for CoAP in IoT

Cited by 8 publications

References 16 publications

A Survey on Congestion Control Protocols for CoAP

A Survey on Congestion Control Protocols for CoAP

A Reliable CoAP Protocol for IoT Communication

An optimization‐based congestion control for constrained application protocol

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