Congestion Control for IoT Using Channel Trust Based Approach

Poddar, Moumita; Chaki, Rituparna; Pal, Debdutta

doi:10.1007/978-3-319-99954-8_33

Cited by 3 publications

(4 citation statements)

References 21 publications

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“…The proposed method is simulated by network simulator NS2. In order to evaluate the performance of the proposed method in the internet of things (IoT) network, the results of the simulation are compared with two methods Poddar et al [7] and CoCoA [18]. The simulation parameters are shown in table 8.…”

Section: Simulation and Resultsmentioning

confidence: 99%

“…Poddar et al [7] presented a congestion control method for IoT using a channel trust based approach. This method uses the node congestion and reliability criteria to determine whether the channel is reliable for packet transfer from source to destination.…”

Section: Related Workmentioning

confidence: 99%

“…After the back off timer (BF T ), it will start sending data to the destination again. The back off timer (BF T ) for each cluster head based on the cluster head priority and calculated by equation (7).…”

Section: Second Phase: Inter-clusters Congestion Controlmentioning

confidence: 99%

“…Congestion control when the input data to a node exceeds its capacity. When sent a large number of packets to a part of the network, congestion occurs and its performance is reduces [7]. Congestion control in computer networks is meant to avoidance the data from being overloaded in the node and thus the Packets loss.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A hierarchical congestion control method in clustered internet of things

Mokhtari

Barati

2022

J Supercomput

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Section: Simulation and Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Second Phase: Inter-clusters Congestion Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A hierarchical congestion control method in clustered internet of things

Mokhtari

Barati

2022

J Supercomput

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Congestion control in internet of things (IoT) using auction theory

Li,

Zhao

2024

Sci Rep

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The Internet of Things (IoT) facilitates data transmission through communication networks, preventing congestion when input data rate exceeds output, and congestion control in computer networks modulates traffic entry. This paper proposes a fusion of auction theory with reinforcement learning as a means of managing congestion in the IoT. The proposed technique seeks to enhance network performance by utilizing object trustworthiness evaluation and auction-based route selection to manage congestion during data routing. The suggested method calculates the believability of objects by analyzing their historical performance in data forwarding and congestion avoidance, utilizing a learning automaton. The auction approach is employed to determine the most efficient ways for transmitting data. The IoT topology is initially organized into a collection of dependable links known as the Connected Dominating Set (CDS). Active objects employ the learning automata model to assess the reliability of their neighbors. The auction model ultimately chooses the optimal route based on characteristics such as credibility, energy, and delay. The experimental results demonstrate that the proposed methodology surpasses existing comparison methods in the initial scenario, exhibiting a 24.13% reduction in energy usage.

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A Hierarchical Congestion Control Method in Clustered Internet of Things

Mokhtari

Barati

2021

Preprint

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Internet of things (IoT) is a modern technology where data can be transmitted to any things (human, animal, or object) over communications networks, whether Internet or intranet. Congestion occurs when the input data rate to the node, higher than the output data rate of node. Congestion control in computer network modulates traffic entry into a network in order to avoid congestive. This paper suggests a method for congestion control in the internet of things in two phases. The first phase is intra-cluster congestion control, which uses two parameters congestion score (CS) and buffer empty space (BES) to congestion avoidance. In this phase based on these two parameters, 9 states are defined to determine the congestion status of each node, and based on these 9 states the appropriate decision is made to the node. The second phase is inter-clusters congestion control. In this phase, after determined cluster head priority, the parameters of back off timer (BFT), waiting time to receive acknowledgment (WTTRACK), sequence number (SEQ) and retransmission counter (RC) are used for congestion control. The proposed congestion control method is simulated by NS-2 software. A comparison between the performance of proposed method and conventional methods shows that applying proposed method results in a significant improvement in average congestion score (CS), packet lost rate, energy consumption and end-to-end delay.

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Congestion Control for IoT Using Channel Trust Based Approach

Cited by 3 publications

References 21 publications

A hierarchical congestion control method in clustered internet of things

A hierarchical congestion control method in clustered internet of things

Congestion control in internet of things (IoT) using auction theory

A Hierarchical Congestion Control Method in Clustered Internet of Things

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