Network Optimization of Online Learning Resources from the Perspective of Knowledge Flow

Li, Jiannan; Lin, Nan

doi:10.3991/ijet.v17i16.33765

Cited by 2 publications

(2 citation statements)

References 22 publications

(23 reference statements)

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“…Typically, this is done in one way to learn more about the relationship between the measured frequency and the window size and round-trip time in a network transmission session [20] or it can be even in an end-to-end fully-informed network with many things that can affect response times [21], for this current study, it dwells on WiMAX fixed network. However, other approach such as effective usage of unused bandwidth [22], network controller effects on operation [23], network optimization and performance analysis [24], as well as the general concerns and challenges of transmission sessions [25] have been addressed as well.…”

Section: Presentation Of the Results And Discussionmentioning

confidence: 99%

Improving the Quality of Service of Fixed WiMAX Networks by Decreasing Application Response Time Using a Distributed Model

Lawal

Ibrahim

Zammarah

2022

Int. J. Interact. Mob. Technol.

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In the most recent few years, there has been a meteoric rise in the number of different wireless networks, as has the demand for wireless data services and multimedia applications. An improvement in quality of service (QoS) is required in order to meet the ever-increasing demand while also providing a service that is of a higher standard. One of the most cutting-edge technologies, known as World Wide Interoperability for Microwave Access (WIMAX), was developed with the quality of service in mind during its development. Despite utilizing the most recent advancements in technology, the WiMAX network continues to struggle with QoS performance issues. A brand new distributed Client-Server model was designed for the fixed WiMAX Network in order to reduce application response time. This was done in order to improve the quality of service performance. In order to make a comparison with the existing centralized model, the performance of the proposed model was analyzed with OPNET Modeler 16.0. According to the findings, the newly proposed distributed Client-Server system is capable of satisfying the requirements set forth by its users owing to an improvement in QoS performance in terms of application response time when compared to the conventional model. The performance of the network was increased by the deployment of more Base Stations (BSs), Subscriber Stations, and the utilization of client-server Base Stations that were chosen by the Nearest Neighborhood Algorithm that was devised

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Section: Presentation Of the Results And Discussionmentioning

confidence: 99%

Improving the Quality of Service of Fixed WiMAX Networks by Decreasing Application Response Time Using a Distributed Model

Lawal

Ibrahim

Zammarah

2022

Int. J. Interact. Mob. Technol.

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“…Thanks to the development of Internet technology, online learning resources have been greatly enriched and now they are a crucial part of contemporary education [1][2][3][4]. Via Internet, students can access massive learning resources, such as course videos, learning materials, exercise questions, and online tutorials [5], however, it is a difficult job for students to choose the right learning resources for themselves A New Methodology for Clustering of Online Learning Resources Based on Students' Learning Styles from such massive amounts of learning resources [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A New Methodology for Clustering of Online Learning Resources Based on Students' Learning Styles

Li¹

2023

Int. J. Emerg. Technol. Learn.

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Recommending learning resources to students according to their respective learning style is conductive to improving learning efficiency, and the clustering and classification of learning resources conduce to reducing learning resource redundancy and duplication and increasing learning resource utilization. However, available methods of learning resource recommendation usually regard students’ learning styles as fixed and invariable, which apparently contradicts reality and may have a negative influence on students’ learning effect. In view of this matter, this paper aims to propose a novel methodology for clustering online learning resources based on student learning style. At first, the specific steps of the new clustering method were given, and a Sharpe model was adopted to analyze the invalid exposure of students’ learning effect and identify students’ learning styles. The learning style coefficient of students was regarded as a dynamic systemic state, which was estimated by the Kalman filter. Then, the Affinity Propagation Clustering (APC) algorithm was adopted to cluster learning resources based on a student learning style distance matrix, and a model of recommended online learning resource combinations was established based on the proposed method. At last, experimental procedures, including learning style evaluation, pretest exam score prediction, posttest exam score prediction, and data analysis, were described in detail, and the validity of the proposed method was verified by experimental results.

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Network Optimization of Online Learning Resources from the Perspective of Knowledge Flow

Cited by 2 publications

References 22 publications

Improving the Quality of Service of Fixed WiMAX Networks by Decreasing Application Response Time Using a Distributed Model

Improving the Quality of Service of Fixed WiMAX Networks by Decreasing Application Response Time Using a Distributed Model

A New Methodology for Clustering of Online Learning Resources Based on Students' Learning Styles

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