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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Traffic prediction in SDN for explainable QoS using deep learning approach.

Getahun Wassie¹, Jianguo Ding², Yihenew Wondie³

¹IP Networking and Mobile Internet, Addis Ababa University, Addis Ababa, Ethiopia. getahunws12@gmail.com.

Scientific Reports

|November 23, 2023

Summary

This summary is machine-generated.

This study develops deep learning models to predict and identify elephant flows, preventing network congestion and improving quality of service (QoS). The models achieved near-perfect accuracy, highlighting packet and byte size as key detection attributes.

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Area of Science:

Computer Science
Network Engineering
Artificial Intelligence

Background:

Increasing multimedia traffic (VOIP, video) demands enhanced Quality of Service (QoS).
Elephant flows cause network congestion, leading to packet loss and delays.
Deep learning offers a promising solution for real-time network traffic management.

Purpose of the Study:

To design and develop advanced traffic prediction models for identifying elephant flows.
To prevent network congestion proactively in Software-Defined Networking (SDN) environments.
To provide explicit model explanations for network administrators using Explainable Artificial Intelligence (XAI).

Main Methods:

Utilized deep learning algorithms: H2O, Deep Autoencoder.
Employed autoML prediction algorithms: XGBoost, Gradient Boosting Machine (GBM), and Gradient Distribution Function (GDF).
Applied Explainable Artificial Intelligence (XAI) for model interpretability.

Main Results:

Achieved high validation accuracy: 99.97% (XGBoost), 99.99% (GBM), and 100% (GDF).
Reported minimal under-construction error: 0.0003952 (XGBoost), 0.001697 (GBM), and 0.00000408 (GDF).
Identified packet size and byte size as critical attributes for elephant flow detection.

Conclusions:

The developed deep learning models effectively predict elephant flows with exceptional accuracy.
XAI enhances model transparency, aiding network administrators in SDN environments.
Proactive identification and management of elephant flows are crucial for maintaining network QoS.