A Bibliometric Analysis and Visualization of Passive Optical Network Research in the Last Decade

Memon, Kamran Ali; Butt, Rizwan Aslam; Mohammadani, Khalid Hussain; Das, Bhagwan; Ullah, Sibghat; Memon, Saleemullah; Ain, Noor Ul

doi:10.1016/j.osn.2020.100586

Cited by 18 publications

(4 citation statements)

References 53 publications

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“…Equation (1) (Memon et al, 2020). where C x and C y indicate the number of times articles x and y were cited together, respectively.…”

Section: Analysis Methods In Citespacementioning

confidence: 99%

Trends, progress and future directions of nanomaterial based sensors: a bibliometric overview

Babu Thomas,

P. Kumar,

James

et al. 2024

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Purpose Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc. Design/methodology/approach In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021. Findings Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development. Research limitations/implications The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development. Originality/value This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

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“…Equation (1) (Memon et al, 2020). where C x and C y indicate the number of times articles x and y were cited together, respectively.…”

Section: Analysis Methods In Citespacementioning

confidence: 99%

Trends, progress and future directions of nanomaterial based sensors: a bibliometric overview

Babu Thomas,

P. Kumar,

James

et al. 2024

View full text Add to dashboard Cite

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“…In [15,16] , the authors claim that ML technology will become an important means to providing indispensable technical support to further increase communication capacity and improve future communication stability by effectively identifying physical impairments in the network [17]. In the new generation passive optical networks (PONs) [18], ML-based algorithms have also been successfully applied, particularly to the load-balancing problem [19].…”

Section: Related Workmentioning

confidence: 99%

A Comprehensive Study of Machine Learning Application to Transmission Quality Assessment in Optical Networks

et al. 2023

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This paper examines applying machine learning to the assessment of the quality of the transmission in optical networks. The motivation for research into this problem derives from the fact that the accurate assessment of transmission quality is key to an effective management of an optical network by a network operator. In order to facilitate a potential implementation of the proposed solution by a network operator, the training data for the machine learning algorithms are directly extracted from an operating network via a control plane. Particularly, this work focuses on the application of single class and binary classification machine learning algorithms to optical network transmission quality assessment. The results obtained show that the best performance can be achieved using gradient boosting and random forest algorithms.

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“…The end-to-end optical-fiber-based connection from a central office to the home, known as Fiber-to-Home (FTTH), has become a reality in the last decade thanks to the emergence of passive optical networks (PONs) [2]. FTTH PON has experienced notable growth in bandwidth support and improved service quality [3], and research on its bandwidth and energy efficiency has become a significant focus VOLUME 11, 2023 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Sleep-Aware Slicing-Based Scheduler (SA-SBS) for Multi-Operators Virtualized Passive Optical Networks

et al. 2023

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Due to the long reach of the next-generation passive optical network (PON), the idea of sharing infrastructure between multiple PON operators has emerged to reduce capital and operational expenditures. However, the standard transmission convergence layer requires an independent virtual bandwidth management process for each operator. Each operator uses a virtual dynamic bandwidth assignment (vDBA) for upstream bandwidth control. An additional bandwidth scheduler is required to create a single physical bandwidth map (phyBW-map) with non-overlapping time slots for each optical network terminal (ONT) or optical network unit (ONU) in the upstream frame. However, the existing slicing-based scheduler (SBS) using dynamic bandwidth assignment schemes does not perform well with the cyclic sleep process (CSP) for energy conservation in PON due to inefficient utilization of the residual bandwidth of the asleep ONUs of an operator. This work introduces an energy-efficient sleep-aware slicing-based scheduler (SA-SBS) for the multi-operator scenario of ten gigabit-capable symmetric PONs (XGS-PONs). Our approach (SA-SBS) achieves 7-10% better energy savings than the existing slicing-based scheduler (SBS) without compromising upstream delays and delay variance. Moreover, we demonstrate that our scheme outperforms the original SBS, resulting in an average delay(s) reduction of up to 28.5% for operators 1, 2, 3, and 4, respectively. Our findings can significantly improve the energy efficiency and latency performance of virtual PONs in multi-operator scenarios, paving the way for a sustainable and reliable communication infrastructure.INDEX TERMS Bandwidth assignment, bandwidth efficiency, energy efficiency, MT-vPON, vPON.

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A Bibliometric Analysis and Visualization of Passive Optical Network Research in the Last Decade

Cited by 18 publications

References 53 publications

Trends, progress and future directions of nanomaterial based sensors: a bibliometric overview

Trends, progress and future directions of nanomaterial based sensors: a bibliometric overview

A Comprehensive Study of Machine Learning Application to Transmission Quality Assessment in Optical Networks

Energy-Efficient Sleep-Aware Slicing-Based Scheduler (SA-SBS) for Multi-Operators Virtualized Passive Optical Networks

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