Design and Development of a Machine Learning-Based Task Orchestrator for Intelligent Systems on Edge Networks
Author:
Affiliation:
1. Department of Electrical, Computer and Software Engineering, Ontario Tech University, Oshawa, ON, Canada
Funder
Natural Sciences and Engineering Research Council of Canada
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10089444.pdf?arnumber=10089444
Reference38 articles.
1. Design and Testing Novel One-Class Classifier Based on Polynomial Interpolation With Application to Networking Security
2. Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
3. Analysis, Design, and Comparison of Machine-Learning Techniques for Networking Intrusion Detection
4. Fuzzy Workload Orchestration for Edge Computing
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1. A collaborative and distributed task management system for real-time systems;2023 IEEE 26th International Symposium on Real-Time Distributed Computing (ISORC);2023-05
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