A Survey on the impact of Connection-Aware Congestion Identification in RLNC-Based Networks on Quality of Service
Автор: Syed Abid Husain, Baswaraj Gadgay, Shubhangi D.C.
Журнал: International Journal of Wireless and Microwave Technologies @ijwmt
Статья в выпуске: 4 Vol.14, 2024 года.
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Wireless multicast networks, especially in the domains of IoT, 5G, and e-health, are experiencing a growing adoption of random linear network coding (RLNC). Nevertheless, the exponential growth of data can lead to congestion problems. This paper presents a review on novel technique called singular value decomposition (SVD) for the identification of network congestion. When SVD combines with statistical concepts like linear regression can to effectively handle large datasets and conduct comprehensive data analytics. The svd improves network performance and reliability by proactively identifying and mitigating congestion. Additionally, it improves the efficiency of data transmission and delivery in different application scenarios.
RLNC(random linear network coding), congestion, SVD(singular value decomposition), LR(linear regression), detection
Короткий адрес: https://sciup.org/15019264
IDR: 15019264 | DOI: 10.5815/ijwmt.2024.04.04
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