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Published in: Computing 12/2022

25-07-2022 | Regular Paper

Intelligent and compliant dynamic software license consolidation in cloud environment

Authors: Leila Helali, Mohamed Nazih Omri

Published in: Computing | Issue 12/2022

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Abstract

Based on the virtualization technology and pushed by the softwarization paradigm and the actual demand for services and resources, commercial cloud data centers know an unprecedented expansion. The systematic presence of software and the services generated enabled the development of the already dense application expenses. This causes, not only a cost explosion, especially when proprietary solutions protected by licenses are in hand, but also, represents a critical need in terms of software asset and resource management at the SaaS level. In addition to these costs, inefficient resource utilization, and the resulting energy represent an important part of the operational expenditure of data centers and are still a hot topic despite the consolidation initiatives put in place. The main objective of the consolidation service is to maximize resource exploitation while minimizing energy consumption and costs, among others. Even so, we have noticed that the reported literature doesn’t treat license management in the cloud environment as a whole, especially, from the resource management perspective and the overwhelming majority of the consolidation work focuses on resource optimization at the IaaS level. Therefore, we propose a reinforcement learning-based scheme that allows efficient use of resources and optimizes costs, energy consumption, and resource wastage, while remaining compliant. The experimental results show that our intelligent consolidator outperforms the baseline approaches according to the evaluation metrics used regardless of the resource heterogeneity and the data center dimensionality.

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Metadata
Title
Intelligent and compliant dynamic software license consolidation in cloud environment
Authors
Leila Helali
Mohamed Nazih Omri
Publication date
25-07-2022
Publisher
Springer Vienna
Published in
Computing / Issue 12/2022
Print ISSN: 0010-485X
Electronic ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-022-01106-0

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