MODELS OPTIMIZATION OF RESOURCES IN CLOUD COMPUTING: A HYBRID APPROACH TO AUTOMATION OF OPERATIONS AND ENERGY SAVING
Maksym Volk, А. М. Бугрій, Ye.I. Kovtun, R.M. Brestovytskyi, B.V. Sorobey, Ya.V. Lobach · Scientific notes of Taurida National V I Vernadsky University Series Technical Sciences · 2024
The article examines resource management methods in cloud systems, emphasising optimising computing processes and automating operations.The main goal of the research is to develop practical approaches to resource management that will ensure reliability, scalability and minimisation of energy consumption in conditions of increasing load on information systems.Today's cloud computing is an important technology that allows organisations to manage resources dynamically to achieve maximum results with minimum costs.The work describes modern architectural solutions that will enable the implementation of cloud technologies and the use of multi-level strategies to optimise the operation of systems.New approaches to virtual machine management and resource allocation are proposed based on load-balancing principles and dynamic scaling of resources according to computing needs.A comparison of different management models of distributed computing, such as centralised and decentralised architectures, is also made.Experimental simulations have shown the high efficiency of the proposed approaches in natural cloud systems, particularly in conditions of different loads, heterogeneous structures and limited resources.Experiments were conducted using open-source software.Simulation results demonstrated that the proposed resource allocation algorithms reduce delays, improve performance, and reduce energy consumption.The results confirm that the proposed methods and architectural solutions can be used to deploy scalable cloud systems, particularly heterogeneous ones, which provide high efficiency and reliability under static and dynamic loads.The conclusions of the work identify promising directions for further research, particularly the introduction of new algorithms to improve resource management in multi-cloud environments.