Comparative Study of TCP Congestion Control Algorithm in IoT

Hussain, S. M. Suhail; Parween, Sultana

doi:10.1109/icac3n53548.2021.9725642

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…In the publication [25], a comprehensive comparative analysis of TCP's congestion control algorithms within the IoT context is outlined. This study assesses 14 different alternatives, delineating their respective benefits and drawbacks.…”

Section: State-of-the-artmentioning

confidence: 99%

“…In such a dynamic ecosystem, effective congestion control becomes imperative to accommodate a diverse range of devices, each potentially employing a different variation of a transport protocol. This involves adapting data transfer speeds in response to network congestion, all while ensuring fairness and sustaining throughput across the network [25].…”

Section: State-of-the-artmentioning

confidence: 99%

See 1 more Smart Citation

Reliably Controlling Massive Traffic between a Sensor Network End Internet of Things Device Environment and a Hub Using Transmission Control Protocol Mechanisms

Kovtun,

Grochla,

Kempa

et al. 2023

Electronics

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The constant growth of Internet of Things traffic is ensured by the ongoing evolution of the hierarchy of all hardware links of sensor networks. At the same time, the implementation of the Edge computing ideology regulates the complexity of the “first-mile” section (from the sensors array to the peripheral server). Here, the authors suggest paying attention to the growing share of massive traffic from target sensors in the total traffic of the sensors array. This circumstance makes it expedient to introduce an additional link to the peripheral server for summarizing massive traffic from target sensors. The authors present a sensor network end IoT device (SNEIoTD), implemented grounded on a reliable and cheap Raspberry Pi computing platform, as such a link. The introduction of this SNEIoTD makes it possible to reduce the probability of information loss from the critical infrastructure of a smart city and increase the flexibility of controlling the massive traffic of the first mile. In this context, the urgent task is the reliable control of information transfer from the SNEIoTD environment to a hub, which the authors formalize based on Transmission Control Protocol (TCP). This article proposes a mathematical model of the interaction of the main mechanisms of the TCP in the form of a queuing system. As part of this model, a semi-Markov process of an information transfer with a unified speed is selected and its stationary distribution is analytically formalized. A computationally efficient information technology for determining the TCP Window Size is formulated, taking into account the interaction of TCP mechanisms in the process of massive traffic control. Using the example of TCP Westwood+ protocol modification, it is shown that the results of the application of information technology permit increases in the stability of data transfer under the circumstances of increasing Round-Trip Times.

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Section: State-of-the-artmentioning

confidence: 99%

Section: State-of-the-artmentioning

confidence: 99%

Reliably Controlling Massive Traffic between a Sensor Network End Internet of Things Device Environment and a Hub Using Transmission Control Protocol Mechanisms

Kovtun,

Grochla,

Kempa

et al. 2023

Electronics

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show abstract

“…However, various challenges are present in IoT data transmission between sensor nodes due to their individual transmission rate which leads to high network congestion [3]. To overcome such challenges Transmission Control Protocol (TCP) which is a transport layer protocol is introduced for efficient data transmission because it transmits huge amount of data traffic globally and is constrained to handle network blockage by reducing the congestion in the IoT environment and also enhances the quality of service (QoS) [4], [5]. This protocol provides effective data transmission with better performance in terms of load, connectivity, reliability, low latency, and speed when compared with user datagram protocol (UDP) [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Cross-Layer based TCP Performance Enhancement in IoT Networks

Parween¹,

Hussain²

2022

IJACSA

Self Cite

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Transmission Control Protocol (TCP) used multiple paths for performing transmission of data simultaneously to improve its performance. However, previous TCP protocols in Internet of Things (IoT) networks experienced difficulty to transmit a greater number of subflows. To overcome the above issues, we introduced cross-layer framework to perform efficient packet scheduling and congestion control for increasing the performance of TCP in IoT networks. Initially, the proposed IoT network is constructed based on grid topology using Manhattan distance which improves the scalability and flexibility of the network. After network construction, packet scheduling is performed by considering numerous parameters such as bandwidth, delay, buffer rate, etc., using fitness based proportional fair (FPF) scheduling algorithm and selecting best subflow to reduce the transmission delay. The scheduled subflow is sent over an optimal path to improve the throughput and goodput. After packet scheduling, congestion control in TCP is performed using cooperative constraint approximation 3 + (CoCoA3 + -TCP) algorithm in which three stages are employed namely congestion detection, fast retransmission, and recovery. The congestion detection in TCP-IoT environment is performed by considering several parameters in which cat and mouse-based optimization (CMO) is utilized to adaptively estimate retransmission timeout (RTO) for reducing the delay and improving the convergence during retransmission. Fast retransmission and recovery are performed to improve the network performance by adjusting the congestion window size thereby avoiding congestion. The simulation of cross-layer approach is carried out using network simulator (NS-3.26) and the simulation results show that the proposed work outperforms high TCP performance in terms of throughput, goodput, packet loss, and transmission delay, jitter, and congestion window size.

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