Author : Nitin Khosla
Affiliation : University of Canberra
Country : Austrlia
Category : Computer Science & Information Technology
Volume, Issue, Month, Year : 10, 05, May, 2020
The aim of a semi-supervised neural net learning approach in this paper is to apply and improve the supervised classifiers and to develop a model to predict CPU usages under unpredictable peak load (under stress conditions) in a large enterprise applications environment with several hundred applications hosted and with large number of concurrent users. This method forecasts the likelihood of extreme use of CPU because of a burst in web traffic mainly due to web-traffic from large number of concurrent users. This model predicts the CPU utilization under extreme load (stress) conditions.
Keyword : Semi-supervised learning, Performance Engineering, Stress testing, Neural Nets, Machine learning applications.
For More Details : https://aircconline.com/csit/papers/vol10/csit100513.pdf