Published Paper Details:

The emergence of cloud computing has revolutionized the Information and Communication Technology landscape, offering a cost-effective and scalable solution for the on-demand provision of computing resources. Organizations are increasingly drawn to the cloud for outsourcing their computational requirements, benefiting from minimal upfront investment. Central to this paradigm are Service Level Agreements (SLAs), which ensure Quality of Service (QoS) between cloud providers and users. The breach of SLAs can result in contractual penalties and revenue loss, underscoring the criticality of effective SLA management for cloud providers. This involves continuous monitoring and control of various SLA parameters to prevent violations. To address this challenge, there is a growing need for proactive measures to anticipate and mitigate potential breaches by predicting SLA parameter values based on continuous monitoring data. In this research, we propose an agent-based SLA management framework featuring a coordinator agent designed to employ predictive modeling techniques for pre-emptively identifying and addressing SLA violations. Our approach is substantiated by a case study utilizing real-world datasets, demonstrating the efficacy of predictive modeling in enhancing SLA management within cloud environments.