A Semantically Rich Framework to Automate Cloud Service Level Agreements

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https://ieeexplore.ieee.org/abstract/document/9678067

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https://doi.org/10.1109/TSC.2022.3140585
 http://hdl.handle.net/11603/24128

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UMBC Information Systems Department

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Author/Creator ORCID

https://orcid.org/0000-0002-6354-1686

Date

2022-01-11

Type of Work

journal articles
preprints
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Program

Citation of Original Publication

D. Natolana Ganapathy and K. P. Joshi, "A Semantically Rich Framework to Automate Cloud Service Level Agreements," in IEEE Transactions on Services Computing, doi: 10.1109/TSC.2022.3140585.

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Subjects

UMBC Ebiquity Research Group

Abstract

Consumers evaluate and choose cloud-based services based on the Service Level Agreements (SLA). These agreements list the service terms and metrics to be agreed upon by the service providers and the customers. Current cloud SLAs are text documents that require significant manual effort to parse and determine if providers meet the SLAs. Moreover, due to the lack of standardization, providers differ in the way they define the terms and metrics, making it more difficult to compare different provider SLAs. We have developed a novel framework to significantly automate the process of extracting knowledge embedded in cloud SLAs and representing it in a semantically rich knowledge graph helping the user to make a calculated decision in choosing a provider. Our framework captures the key terms, measures, and deontic rules, in the form of obligations and permissions present in the cloud SLAs. In this paper, we discuss our framework, technique, and challenges in automating the cloud services agreement. We also describe our results and their validation against well-established standards.