Feedback Control loops for performance SLAs in Cloud Computing

Ansari, Ammar Naeemul Haque (2024) Feedback Control loops for performance SLAs in Cloud Computing. Masters thesis, Dublin, National College of Ireland.

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Abstract

Cloud computing indeed changed the ball game in how businesses deploy and manage applications by offering resources that are scalable with flexible pricing models. Ensuring SLA in dynamic cloud environments is still one of the biggest challenges because workload patterns are usually unpredictable. This research investigates the use of feedback control loops to optimize resource provisioning for SLA assurance in such an environment. The paper investigates first the state-of-the-art optimization techniques, including PID controllers and machine learning models, for dynamic resource allocation. We will provide the critical review of the related strengths and weaknesses, identify the deficiencies in the adaptiveness of the existing approaches to real-time changes in workload while keeping computations efficient. Our contribution incorporates an integrated approach, including predictive analytics, anomaly detection, and robust optimization methods. The major contributions of the work are lightweight predictive models developed for resource usage forecasting and the implementation of mechanisms for anomaly detection in order to proactively prevent SLA violations. It further proposes a robust hybrid cloud management strategy for heterogeneous platforms to handle resource allocation challenges w.r.t. cost efficiency and reliability. The framework is then validated using real workload data, which has given great improvements in SLA adherence and resource utilization. This research addresses not only current limitations in cloud resource management but also lays the foundation for future research into autonomous cloud systems. The proposed framework enables a scalable and adaptive solution to manage complex workloads and contributes to both academic knowledge and practical applications in cloud computing.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Kazmi, Aqeel UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	14 Jul 2025 14:14
Last Modified:	14 Jul 2025 14:14
URI:	https://norma.ncirl.ie/id/eprint/8080

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