The bottleneck problem in large scale IEEE 802.15.4/ZigBee networks

Chao, Chih Min; Wang, Hsin Hsiang

doi:10.1504/ijahuc.2017.086263

Cited by 4 publications

(3 citation statements)

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“…In [30], the single-channel MAC protocol is proposed using a grid limit to save on energy. Although this protocol tries to boost network longevity by increasing nodes' sleeping time, in high traffic, it leads to higher collision and frame resubmitting and hence higher energy consumption in the network because it only utilizes one channel.…”

Section: B Popular Congestion Control Methods 1) Congestion Control mentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms. INDEX TERMS Internet of Things, wireless sensor network, congestion control, fuzzy decision making, and back-pressure.

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Section: B Popular Congestion Control Methods 1) Congestion Control mentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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“…Using the IEEE 802.11AH standard as a backbone for the network through the intermediate gateway is expected to help with the bottleneck problem. This happens in largescale IEEE 802.15.4 networks when all the traffic from the nodes have to go through a single point which cannot accommodate all this traffic appropriately, thus the nodes closer to the main coordinator will have a heavier traffic burden [28]. In the homogeneous network case, those nodes are the 6LoWPAN cluster heads and the 6LoWPAN part in the edge gateway.…”

Section: 1mentioning

confidence: 99%

Enhancing the Performance of 6LoWPAN-Based Wireless Sensor Networks (WSNs) with IEEE 802.11AH (Wi-Fi HaLow)

Astour,

Saleh

2023

Wireless Communications and Mobile Computing

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6LoWPAN allows IEEE 802.15.4 standard-based wireless sensor networks (WSNs) to be connected to the Internet through the Internet protocol IPv6; however, its performance decreases as the network grows in size due to complications such as the bottleneck problem; therefore this paper aims to improve the performance of 6LoWPAN-based WSNs by using the IEEE 802.11AH standard as a backbone in these networks, since this emerging new technology is suitable for IoT applications, as it can provide a coverage range up to 1,000 m and data transmission rates up to 78 Mbps. The IEEE 802.11AH standard can be used as a backbone by utilizing its characteristics to improve some of the performance parameters of the 6LoWPAN networks such as end-to-end delay, frames delivery ratio, and the network throughput. This paper proposes a heterogeneous network infrastructure consisting of 6LoWPAN and the IEEE 802.11AH standard to enable bidirectional data transmission between the network components and the Internet via the Internet protocol IPv6 with two types of gateways, the edge gateways to connect the entire network to the Internet and the intermediate gateways to connect the 6LoWPAN clusters to the edge gateways. The simulation results demonstrate that the heterogeneous network approach can provide significant improvement gains compared to the 6LoWPAN homogeneous networks, since it shows clear improvements to the packets delivery ratio, the end-to-end delay mean value and the network throughput, subsequently leading to a distinct enhancement in the network’s overall reliability.

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“…The traditional single-channel protocol (Huang et al, 2013;Guntupalli et al, 2017;Yu and Yang, 2018;Liu and Chung, 2011) has been unable to satisfy certain basic network requirements, such as low power consumption, high reliability and high throughput. The research in Chao and Wang (2017) analyses the bottleneck problem when there are many data to deliver during the data gathering process in large-scale WSNs. Therefore, many multichannel protocols have been proposed to achieve better performance for less power consumption (Liew et al, 2018) and lower transmission latency (Li et al, 2015;Nguyen et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Performance optimisation of multichannel MAC in large-scale wireless sensor network

Dong¹,

Shi²,

Yu³

2022

IJSNET

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Efficient multichannel medium access control (MAC) protocols can significantly prolong the lifetime of sensor networks. In this paper, an energy-efficient prediction-based multichannel MAC protocol (PM-MAC) is proposed for large-scale wireless sensor networks (WSNs). PM-MAC minimises sensor node's idle listening time without introducing any multihop time synchronisation and channel assignment overhead by introducing a prediction mechanism of the target node's wakeup channel and wakeup time. PM-MAC introduces a dynamic channel allocation to achieve precise and quick resynchronisation when a prediction error occurs. In addition, in PM-MAC, the load can be well balanced on all channels. Finally, its prediction-based retransmission mechanism can achieve more energy efficiency in resolving severe wireless collisions caused by concurrent traffic in large-scale sensor network. The PM-MAC not only reduces multihop packet latency and energy consumption, but also increases network capacity and throughput. Experimental results confirm the outstanding performance of PM-MAC in all testbeds.

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The bottleneck problem in large scale IEEE 802.15.4/ZigBee networks

Cited by 4 publications

References 0 publications

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

Enhancing the Performance of 6LoWPAN-Based Wireless Sensor Networks (WSNs) with IEEE 802.11AH (Wi-Fi HaLow)

Performance optimisation of multichannel MAC in large-scale wireless sensor network

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