SLO-ML : A Language for Service Level Objective Modelling in Multi-cloud applications

Elhabbash, Abdessalam and Jumagaliyev, Assylbek and Blair, Gordon and Elkhatib, Yehia (2019) SLO-ML : A Language for Service Level Objective Modelling in Multi-cloud applications. In: Proceedings of IEEE/ACM 12th International Conference on Utility and Cloud Computing :. IEEE/ACM, 241–250. ISBN 9781450368940

[thumbnail of Elhabbash2019sloml]
Text (Elhabbash2019sloml)
Elhabbash2019sloml.pdf - Accepted Version

Download (3MB)


Cloud modelling languages (CMLs) are designed to assist customers in tackling the diversity of services in the current cloud market. While many CMLs have been proposed in the literature, they lack practical support for automating the selection of services based on the specific service level objectives of a customer's application. We put forward SLO-ML, a novel and generative CML to capture service level requirements. Subsequently, SLO-ML selects the services to honour the customer's requirements and generates the deployment code appropriate to these services. We present the architectural design of SLO-ML and the associated broker that realises the deployment operations. We evaluate SLO-ML using an experimental case study with a group of researchers and developers using a real-world cloud application. We also assess SLO-ML's overheads through empirical scalability tests. We express the promises of SLO-ML in terms of gained productivity and experienced usability, and we highlight its limitations by analysing it as application requirements grow.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in UCC'19: Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing 2019
ID Code:
Deposited By:
Deposited On:
04 Nov 2019 11:50
Last Modified:
16 Jul 2024 04:48