Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

Technological University Dublin

2022

Machine learning

Articles 1 - 3 of 3

Full-Text Articles in Engineering

Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin May 2022

Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin

Articles

Traffic classification is a crucial aspect for Software-Defined Networking functionalities. This paper is a part of an on-going project aiming at optimizing power consumption in the environment of software-defined datacenter networks. We have developed a novel routing strategy that can blindly balance between the power consumption and the quality of service for the incoming traffic flows. In this paper, we demonstrate how to classify the network traffic flows so that the quality of service of each flow-class can be guaranteed efficiently. This is achieved by creating a dataset that encompasses different types of network traffic such as video, VoIP, game …


Detecting Iot Attacks Using An Ensemble Machine Learning Model, Vikas Tomar, Sachin Sharma Mar 2022

Detecting Iot Attacks Using An Ensemble Machine Learning Model, Vikas Tomar, Sachin Sharma

Articles

Malicious attacks are becoming more prevalent due to the growing use of Internet of Things (IoT) devices in homes, offices, transportation, healthcare, and other locations. By incorporating fog computing into IoT, attacks can be detected in a short amount of time, as the distance between IoT devices and fog devices is smaller than the distance between IoT devices and the cloud. Machine learning is frequently used for the detection of attacks due to the huge amount of data available from IoT devices. However, the problem is that fog devices may not have enough resources, such as processing power and memory, …


A Hybrid Machine Learning Technique For Feature Optimization In Object-Based Classification Of Debris-Covered Glaciers, Shikha Sharda, Mohit Srivastava, Hemendra Singh Gusain, Naveen Kumar Sharma, Kamaljit Singh Bhatia, Mohit Bajaj, Harsimrat Kaur, Hossam Zawbaa, Salah Kamel Jan 2022

A Hybrid Machine Learning Technique For Feature Optimization In Object-Based Classification Of Debris-Covered Glaciers, Shikha Sharda, Mohit Srivastava, Hemendra Singh Gusain, Naveen Kumar Sharma, Kamaljit Singh Bhatia, Mohit Bajaj, Harsimrat Kaur, Hossam Zawbaa, Salah Kamel

Articles

Object-based features like spectral, topographic, and textural are supportive to determine debris-covered glacier classes. The original feature space includes relevant and irrelevant features. The inclusion of all these features increases the complexity and renders the classifier’s performance. Therefore, feature space optimization is requisite for the classification process. Previous studies have shown a rigorous exercise in manually selecting the best combination of features to define the target class and proven to be a time consuming task. The present study proposed a hybrid feature selection technique to automate the selection of the best suitable features. This study aimed to reduce the classifier’s …