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User-centric adaptation of multi-tenant services: preference-based analysis for service reconfiguration

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conference contribution
posted on 2014-06-23, 15:44 authored by Jesús García-Galán, Liliana Pasquale, Pablo Trinidad, Antonio Ruiz-Cortés
Multi-tenancy is a key pillar of cloud services. It allows dif- ferent tenants to share computing resources transparently and, at the same time, guarantees substantial cost savings for the providers. However, from a user perspective, one of the major drawbacks of multi-tenancy is lack of con gura- bility. Depending on the isolation degree, the same service instance and even the same service con guration may be shared among multiple tenants (i.e. shared multi-tenant ser- vice). Moreover tenants usually have di erent - and in most of the cases - con icting con guration preferences. To over- come this limitation, this paper introduces a novel approach to support user-centric adaptation in shared multi-tenant services. The adaptation objective aims to maximise ten- ants' satisfaction, even when tenants and their preferences change during the service life-time. This paper describes how to engineer the activities of the MAPE loop to sup- port user-centric adaptation, and focuses on the analysis of tenants' preferences. In particular, we use a game theoretic analysis to identify a service con guration that maximises tenants' preferences satisfaction. We illustrate and motivate our approach by utilising a multi-tenant desktop scenario. Obtained experimental results demonstrate the feasibility of the proposed analysis.

Funding

Study on Aerodynamic Characteristics Control of Slender Body Using Active Flow Control Technique

Japan Society for the Promotion of Science

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History

Publication

SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems;pp. 65-74

Publisher

Association for Computing Machinery

Note

peer-reviewed

Other Funding information

FEDER, SFI, ERC

Rights

"© ACM, 2014. 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 SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, pp. 65-74, http://dx.doi.org/10.1145/2593929.2593930

Language

English

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