Application of Neural Networks in Distribution of the Load in Cluster-Based Web Systems
Source abstract
Abstract
Cloud computing systems revolutionized the Internet, and web systems in particular. Quality of service is the basis of resource configuration management in the cloud. Load balancing mechanisms are implemented in order to reduce costs and increase the quality of service. The usage of those methods with adaptive intelligent algorithms can deliver the highest quality of service. In this article, the method of load distribution using neural networks to estimate service times is presented. The discussed and conducted research and experiments include many approaches, among others, application of a single artificial neuron, different structures of the neural networks, and different inputs for the networks. The results of the experiments let us choose a solution that enables effective load distribution in the cloud. The best solution is also compared with other intelligent approaches and distribution methods often used in production systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cloud Computing and Resource Management · Wireless Sensor Networks for Data Analysis · Cybersecurity and Information Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science, Opole University of Technology, Proszkowska 76, 45-758 Opole, Poland
References (48)
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