Fog computing, Software Define Networking, RESTful API and Machine learning are new technologies in the area of ICT as well as in Networking. Fog computing brought high performance computing at the edge of network and...
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ISBN:
(纸本)9783031807121;9783031807138
Fog computing, Software Define Networking, RESTful API and Machine learning are new technologies in the area of ICT as well as in Networking. Fog computing brought high performance computing at the edge of network and Software Defined networking. As we intended to head towards QoS and Load balancing in SDN. In this work we cover an initial segment which is Machine leaning model implementation on a network traffic information to predict future outcomes for traffic flow. Meanwhile, in comprehensive research we intended to reduce network congestion, jitter, QoS and load balancing by learning past traffic flow information. As well as, we aim to improve maximum utilization of link-bandwidth. Through RESTful API of SDN, we can embed Machine learning based prediction model to the network server which can modify the network policies by learning from past experiences. In this paper, we proposed a QoS and load balancing framework. A Server and SDN based application for network monitoring, management and controlling the policies over network gateway for better performance in regard of traffic flow. Experiment result shows that implementation of Machine learning over network traffic flow information immensely important for new emerging technologies. The evaluation results of Machine learning model we implemented in this work depicts that model performs well. Meanwhile the model improves by increasing with the number of epochs.
The proceedings contain 49 papers. The special focus in this conference is on Frontiers of Intelligent computing: Theory and Applications. The topics include: Nepali Word Spelling Correction Using Ensemble learning Te...
ISBN:
(纸本)9789819601462
The proceedings contain 49 papers. The special focus in this conference is on Frontiers of Intelligent computing: Theory and Applications. The topics include: Nepali Word Spelling Correction Using Ensemble learning Technique;the Impact of Information Security Policies and Innovations in Digital Technology on the Transformation of Healthcare in Developing Nations: A Literature Review;integrating Multi-omics and Clinical Narratives for Predictive Modeling: Genomics, Transcriptomics, Proteomics, and Medical Texts in Disease Analysis;a Comprehensive Survey of Fake Review Detection Technology;a Hybrid Intelligent Decision Support System for Automating Financial Credit Evaluation;Advancing Taxation in the New Era: Enhancing Tax Ratios with the Core Tax Administration System (CTAS);Enabling Grid Stability: Harnessing μPMU Data for Data-Driven Analysis of Grid Frequency Events;machine learning Techniques to Detect Fake News on Social Media: A Systematic Review;cutting-Edge Technology-Based Social Enterprises in India for Sustainable, Inclusive Healthcare;enhancing Telugu Sarcasm Classification Models with Word Embeddings in Imbalanced Datasets;capital Punishment: Analyzing Trends in the United States (1976–2016);exploring the Technostress Issue Among Indonesian Young Entrepreneurs;teaching Computer Science Using Cloud-Based IDE with Perspectives in Inclusivity;Comparison of Data Encryption Standard (DES) and Advanced Encryption Standard (AES) in Security Issues of Cloud computing: A Literature Review;enhancing Corporate and Factory Training Through Game Development: A Comparative Review;usability of Intelligent System in Implementing Tutoring Lesson in Education: A Literature Review;performance Efficiency of Cloud computing—A Literature Review;decentralized Finance (DeFi) Wallets: A Review of its Efficiency, Usability, and Effectiveness;Social Networks on WEB 3.0.
Until the early 2020s, conventional face-to-face lectures were the set standard for imparting knowledge to a large crowd of students at universities. However, when the pandemic as a drastic event changed the world ove...
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For maximum crop productivity, leaf disease classification and early identification are essential. Conventional methods for identifying illness need a lot of time and money. Promising results have been observed in the...
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It is the information age thus;it is very important to understand how to personalize content in accordance with what appeals to a user. This work is conceptualized to be labeled 'Tailoring Content with Keyword-Bas...
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Python is built with very few data types and constructs. Drawing on an earlier approach to learning spoken language through picture comparisons, we propose to teach and learn Python similarly, By using simple diagrams...
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Proton Exchange Membrane Fuel Cells (PEMFCs) play a vital role in the transition to clean energy technologies, requiring accurate and efficient models for their control, optimization, and real-time monitoring. This re...
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The Satellite computing System (SCS) faces an increasing number of attacks. Although Moving Target Defense (MTD) can effectively mitigate attacks in ground networks, it is not well-suited for SCS due to the highly dyn...
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Analyzing dairy cattle behavior and anomalies is a critical component of precision livestock farming, allowing farmers to remotely monitor animals for health and behavior. In order to accomplish this task better, the ...
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This paper introduces a hybrid deep learning model, DABNet, to tackle the challenge of poor accuracy in acne classification as a result of insufficient training data availability. The presented work employed a Deep Co...
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