Congestion control mechanism for Internet-of-Things (IOT) paradigm

Halim, N.H.; Yaakob, Naimah; Isa, Azmi Bin Awang Md

doi:10.1109/iced.2016.7804663

Cited by 11 publications

(5 citation statements)

References 15 publications

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“…Hamimi et al [16] proposed the congestion control mechanism for internet of things (IoT) paradigm. The purpose of this approach is to reduce the number of closed losses during transmission and minimize the number of visits to reduce the corresponding cost, energy and response time.…”

Section: Related Workmentioning

confidence: 99%

A hierarchical congestion control method in clustered internet of things

Mokhtari

Barati

2022

J Supercomput

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Section: Related Workmentioning

confidence: 99%

A hierarchical congestion control method in clustered internet of things

Mokhtari

Barati

2022

J Supercomput

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“…Several flow control and congestion control algorithms are proposed for IoT paradigm. A mechanism for congestion control in IoT called packet discarding based on node clustering (PDNC) is suggested in [22], where congestion is controlled by discarding selected packets. The packets to discard are based on data size larger than 60 bytes or with time to live field 0.…”

Section: Related Workmentioning

confidence: 99%

Priority based flow control protocol for internet of things built on light fidelity

Vatsala

Chitradurga

2022

IJECE

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<span>Excessive usage of Internet by most of the applications that use internet of things (IoT) has resulted in need for high bandwidth network. Light fidelity (LiFi) is one such network having bandwidth in terms of GigaHertz, but LiFi has a limited propagation range hence it can be deployed only in the local area. When IoT nodes are connected using LiFi network in the local area they start pushing large data to the cloud there by arising need for flow control. Some of the IoT applications such as patient monitoring systems and nuclear systems, generate critical data. The protocol for flow control in this case should be based on priority of data since critical data with high priority have to be transmitted first. We develop a flow control protocol named priority based flow control protocol (PFCP) by providing priority to flows that carry critical data especially in IoT system that use LiFi network. We evaluate performance of different transmission control protocol (TCP) variants and modify TCP variant that yields maximum goodput according to the priority based protocol developed and demonstrate that flows that carry critical data are given priority compared to non-prioritized flows</span>

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“…Moreover, the queuing discipline used for their test has been the sole DropTail, which is not enough for an accurate congestion control treatment. An even more focused work is [27] in which the authors described in detail their congestion control mechanism designed for IoT, in particular, they implement a packet discarding technique using WSN architecture knowledge. Unfortunately, even in this case, no state-of-the-art comparison support the results, no cross comparison with AQM and TCP is provided, and the old ns2 is used for testing platform leading to a lack of transparency.…”

Section: Related Workmentioning

confidence: 99%

Which AQM fits IoT better?

Grazia

Patriciello

Klapez

et al. 2017

2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI)

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Most of the Internet traffic is carried by Transmission Control Protocol (TCP) nowadays, even in the case of real-time services and IoT environments. A key point of each TCP variant that defines the specific variant trademark is the congestion control algorithm. This congestion control, alone, is not able to mitigate the congestion problem completely; the most efficient solution, to be coupled with it, is the Active Queue Manager (AQM). In this paper, we analyze the response to congestion provided by the novel AQMs when coupled with popular TCP variants and, has happened in IoT networks, with a mix of TCP variants simultaneously active on the network. We provide extensive simulations within ns-3 to highlight what is the better AQM solution for IoT networks by considering the TCP algorithm and other environmental conditions like the number of active nodes, the network RTT and the presence of multiple RTT flows. We collected network metrics like throughput, goodput, latency, RTT variation, flows' fairness and a simple drop analysis.

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Congestion control mechanism for Internet-of-Things (IOT) paradigm

Cited by 11 publications

References 15 publications

A hierarchical congestion control method in clustered internet of things

A hierarchical congestion control method in clustered internet of things

Priority based flow control protocol for internet of things built on light fidelity

Which AQM fits IoT better?

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