Predictive Modeling of Service Level Agreement Parameters for Cloud Services


Seema Sunil Chowhan
Shailaja Shirwaikar
Ajay Kumar


Cloud computing has emerged as an important paradigm in Information and Communication Technology space by enabling cost effective, on demand provisioning of elastic computing resources. With limited or almost negligible upfront investment, lots of organizations are attracted towards cloud, for outsourcing their computational needs. Service Level Agreements (SLA) between Cloud providers and the Cloud users are used to assure Quality of Service (QoS) which is one of the big issues that resists organization from availing cloud resources. SLA management is thus an important activity for Cloud providers as SLA violations may lead to contractual penalties and in turn loss of revenue and customer base. Managing SLA involves constant monitoring and controlling various SLA parameters. Therefore, it is desirable for providers to control possible violations before they happen by predicting the values of SLA parameters using the values continuously measured over a time period. We present an agent based SLA-management with design of a coordinator agent that uses a predictive modeling approach for predicting and mitigating SLA violations. The design is based on a case study on available datasets containing measurements on web services of SLA parameters such as response time and throughput.


How to Cite
Seema Sunil Chowhan, Shailaja Shirwaikar, & Ajay Kumar. (2016). Predictive Modeling of Service Level Agreement Parameters for Cloud Services. International Journal of Next-Generation Computing, 7(2), 115–129.


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