Performance Optimization of the IEEE 802.15.4-Based Link Quality Protocols for WBASNs/IoTs in a Hospital Environment Using Fuzzy Logic

Akbar, Muhammad Sajjad; Yu, Hongnian; Cang, Shuang

doi:10.1109/jsen.2019.2900009

Cited by 13 publications

(2 citation statements)

References 50 publications

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“…Aiming at the problem of insufficient reliability of IEEE 802.15.4 link quality protocol in hospital environment, Akbar et al [13] proposed a link quality prediction method based on fuzzy logic. First, the thresholds of LQI and RSSI of different link qualities in different hospital environments were obtained through experiments.…”

Section: Lqp Based On Linkmentioning

confidence: 99%

Light Gradient Boosting Machine-Based Link Quality Prediction for Wireless Sensor Networks

Liu

Niu

Zhang

et al. 2022

Wireless Communications and Mobile Computing

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Link quality prediction is a fundamental component of the wireless network protocols and is essential for routing protocols in wireless sensor networks (WSNs). Effective link quality prediction can select high-quality links for communication and improve the reliability of data transmission. In order to improve the accuracy of the link quality prediction model and reduce the model complexity, the link quality prediction model based on the light gradient boosting machine (LightGBM-LQP) is proposed in this paper. Specifically, agglomerative hierarchical clustering and manual division are combined to grade the link quality and obtain the labels of samples. Then, light gradient boosting machine (LightGBM) classification algorithm and Focal Loss are used to estimate the link quality grades. In order to reduce the impact of data imbalance, Borderline-SMOTE is employed to oversample the minority link quality samples. Finally, LightGBM-LQP predicts link quality grade at the next moment with historical link quality information. The experimental results on data collected from a real-world WSNs show that the proposed model has better prediction accuracy and shorter predicting time compared to related models.

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Section: Lqp Based On Linkmentioning

confidence: 99%

Light Gradient Boosting Machine-Based Link Quality Prediction for Wireless Sensor Networks

Liu

Niu

Zhang

et al. 2022

Wireless Communications and Mobile Computing

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show abstract

“…The diverse connectivity between industrial field devices and edge infrastructure, depending on the communication medium and protocols from the media access control (MAC) layer all the way toward the application layer as defined in the open systems interconnection (OSI) model, leads to widely divergent performance. Many researchers have provided thorough study on the performance of existing industrial connectivity protocols from different perspectives, such as IEEE 802.11 [10], [11], IEEE 802.15.4 [12], [13], ISA100.11a [14], [15], WIA-PA [16], [17], wirelessHART [18], [19], Thread [20], [21], and LoRaWAN [22]- [24], whereas the performance of the backbone, i.e., the edge-cloud computing stack, is still unknown. Therefore, in this study, we limit our scope to the performance of containerization-based edge-cloud computing stacks in IIoT applications.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective

Liu

Lan

Pang

et al. 2021

IEEE Open J. Ind. Electron. Soc.

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Today, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry to implement edge-cloud computing infrastructures. Has the performance of the container-based edge-cloud computing stacks reached industry requirement? In this paper, from the industrial client perspective, we provide a performance evaluation methodology and apply it to the state-of-the-art containerization-based edge-cloud computing infrastructures. The influences of the message sending interval, payload, network bandwidth and concurrent devices on full stack latency are measured, and the processing capability of executing machine learning tasks are benchmarked. The results show that containerization on the edge does not introduce noticeable performance degradation in terms of communication, computing and intelligence capabilities, making it a promising technology for the edge-cloud computing paradigm. However, there is a large room for performance improvement between current implementation of the edge-cloud infrastructure and the demanding requirements anticipated by time-critical industrial applications. We also emphasize and showcase that partitioning of an industrial application into microservices throughout the whole stack can be considered during solution design. The proposed evaluation methodology can be a reference to users of edge-cloud computing as well as developers to get a client perspective overview of system performance.

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Modeling and analysis of priority and range‐based‐deterministic and synchronous multichannel extension‐guaranteed time slot allocation in IEEE 802.15.4e medium access control protocol

Asuti

Basarkod

2021

Trans Emerging Tel Tech

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Internet of Things (IoT) enabled technology in the current applications such as smart grids, smart cities, and smart health sectors utilize wireless sensor networks (WSN) to establish stable and reliable communication between the nodes. Moreover, the primary requirement of WSN in IoT applications is to provide low-rate data communication. The IEEE 802.15.4e standard-based medium access control (MAC) protocol is found suitable for low-rate data communication in WSN. The IEEE 802.15.4e standard adopts a deterministic and synchronous multichannel extension (DSME) MAC protocol which employs a multisuperframe structure with multichannel data transmission during the contention free period. However, the guaranteed time slot (GTS) allocation process in DSME employed by the standard may not be suitable for an adaptive traffic network scenario that has a direct impact on the throughput and bandwidth utilization. In this article, we develop a priority and range-based DSME-GTS allocation algorithm based on the priorities of end nodes and range estimation. Furthermore, the proposed algorithm is developed for the two types of network scenarios encountered in a star topology-enabled WSN. In scenario-1, the slots allocation process is carried out based on the priorities of end nodes.Next, in scenario-2, the slots allocation process is carried out based on the range estimation of end nodes. Detailed mathematical modeling of the proposed methodology is provided for the various performance metrics. The model is validated using the MATLAB 2017a programming tool. Simulation results show that the proposed methodology outperforms the existing DSME-GTS approaches in terms of performance metrics such as packet delivery ratio, end-to-end delay, packet loss ratio, throughput, delay, bandwidth utilization, and the energy consumption.

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Performance Optimization of the IEEE 802.15.4-Based Link Quality Protocols for WBASNs/IoTs in a Hospital Environment Using Fuzzy Logic

Cited by 13 publications

References 50 publications

Light Gradient Boosting Machine-Based Link Quality Prediction for Wireless Sensor Networks

Light Gradient Boosting Machine-Based Link Quality Prediction for Wireless Sensor Networks

Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective

Modeling and analysis of priority and range‐based‐deterministic and synchronous multichannel extension‐guaranteed time slot allocation in IEEE 802.15.4e medium access control protocol

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