In this study, we developed an accurate lightweight machine learning tool to predict end-to-end packet retransmission in science flows of arbitrary size. We ...
In this study, we develop a lightweight machine learning tool to predict end-to-end packet retransmission in science flows of arbitrary size. We also identify ...
Aug 6, 2024 · In this paper, we explored the application of machine learning models to predict and differentiate between congestive and non-congestive packet losses in a ...
Two ML based model are used to predict packet loss, Decision Tree model and Logistics Regression model.
A machine learning approach for packet loss prediction in science flows ; Journal: Future Generation Computer Systems, 2020, p. 190-197 ; Publisher: Elsevier BV.
The experiments show that a suitable machine learning model is able to predict network jitter and packet loss rate relatively accurately for a specific network ...
Aug 6, 2024 · Our results demonstrate that Random Forest and K-Nearest Neighbor classifiers perform better in predicting the type of packet loss, offering a ...
Missing: approach | Show results with:approach
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Giannakou et al. [17] proposed a machine learning approach to predict packet losses in science flows. Liu et al. [18] designed a packet loss estimation method ...
A new lightweight method for TCP throughput prediction using Support Vector Regression (SVR) is described, based on both prior file transfer history and ...
In this paper, we explore a novel approach to end-to-end round-trip time (RTT) estimation using a machine-learning technique known as the Experts Framework.