Dynamic Modelling of Tactics Impact on the Stability of Self-aware Cloud Architectures

Maria Salama; Ahmed Shawish; Rami Bahsoon

doi:10.1109/CLOUD.2016.0126

Dynamic Modelling of Tactics Impact on the Stability of Self-aware Cloud Architectures

Maria Salama, Ahmed Shawish, Rami Bahsoon

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Given the elasticity, on-demand nature, and runtime dynamics of the cloud, a stable self-adaptive architecture should keep the fulfilment of Quality of Service objectives stable, while performing stable adaptations that converge towards these objectives. The dynamic management and selection of architectural tactics, as adaptation mechanisms, shall be in the heart of the adaptation process, as being essential for effective and stable adaptations. This calls for measuring the impact of tactics on the stability of inter-related quality attributes during run-time. In this paper, we introduce a Markovian-based analytical model for dynamically assessing the impact of tactics on the stability behaviour of self-adaptive cloud architectures. The model also employs self-awareness capabilities for betterinforming the selection of optimal tactics configurations leading to stability. Experimental evaluations have shown the accuracy and efficiency of the model in measuring and predicting the impact of tactics on stabilising the Quality of Service provision and the adaptation process.

Original language	English
Title of host publication	2016 IEEE 9th International Conference on Cloud Computing
Publisher	IEEE Computer Society Press
Pages	871-875
Number of pages	5
ISBN (Print)	978-1-5090-2619-7
DOIs	https://doi.org/10.1109/CLOUD.2016.0126
Publication status	Published - Aug 2016
Event	The 9th IEEE International Conference on Cloud Computing - San Francisco, United States Duration: 27 Jun 2016 → 2 Jul 2016

Conference

Conference	The 9th IEEE International Conference on Cloud Computing
Country/Territory	United States
City	San Francisco
Period	27/06/16 → 2/07/16

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10.1109/CLOUD.2016.0126

Salama_et_al_Dynamic_Modelling_Tactics_Impact_Conference_Cloud_Computing
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Cite this

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title = "Dynamic Modelling of Tactics Impact on the Stability of Self-aware Cloud Architectures",

abstract = "Given the elasticity, on-demand nature, and runtime dynamics of the cloud, a stable self-adaptive architecture should keep the fulfilment of Quality of Service objectives stable, while performing stable adaptations that converge towards these objectives. The dynamic management and selection of architectural tactics, as adaptation mechanisms, shall be in the heart of the adaptation process, as being essential for effective and stable adaptations. This calls for measuring the impact of tactics on the stability of inter-related quality attributes during run-time. In this paper, we introduce a Markovian-based analytical model for dynamically assessing the impact of tactics on the stability behaviour of self-adaptive cloud architectures. The model also employs self-awareness capabilities for betterinforming the selection of optimal tactics configurations leading to stability. Experimental evaluations have shown the accuracy and efficiency of the model in measuring and predicting the impact of tactics on stabilising the Quality of Service provision and the adaptation process.",

author = "Maria Salama and Ahmed Shawish and Rami Bahsoon",

year = "2016",

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doi = "10.1109/CLOUD.2016.0126",

language = "English",

isbn = "978-1-5090-2619-7",

pages = "871--875",

booktitle = "2016 IEEE 9th International Conference on Cloud Computing",

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note = "The 9th IEEE International Conference on Cloud Computing ; Conference date: 27-06-2016 Through 02-07-2016",

}

Salama, M, Shawish, A & Bahsoon, R 2016, Dynamic Modelling of Tactics Impact on the Stability of Self-aware Cloud Architectures. in 2016 IEEE 9th International Conference on Cloud Computing. IEEE Computer Society Press, pp. 871-875, The 9th IEEE International Conference on Cloud Computing, San Francisco, United States, 27/06/16. https://doi.org/10.1109/CLOUD.2016.0126

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AU - Bahsoon, Rami

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N2 - Given the elasticity, on-demand nature, and runtime dynamics of the cloud, a stable self-adaptive architecture should keep the fulfilment of Quality of Service objectives stable, while performing stable adaptations that converge towards these objectives. The dynamic management and selection of architectural tactics, as adaptation mechanisms, shall be in the heart of the adaptation process, as being essential for effective and stable adaptations. This calls for measuring the impact of tactics on the stability of inter-related quality attributes during run-time. In this paper, we introduce a Markovian-based analytical model for dynamically assessing the impact of tactics on the stability behaviour of self-adaptive cloud architectures. The model also employs self-awareness capabilities for betterinforming the selection of optimal tactics configurations leading to stability. Experimental evaluations have shown the accuracy and efficiency of the model in measuring and predicting the impact of tactics on stabilising the Quality of Service provision and the adaptation process.

AB - Given the elasticity, on-demand nature, and runtime dynamics of the cloud, a stable self-adaptive architecture should keep the fulfilment of Quality of Service objectives stable, while performing stable adaptations that converge towards these objectives. The dynamic management and selection of architectural tactics, as adaptation mechanisms, shall be in the heart of the adaptation process, as being essential for effective and stable adaptations. This calls for measuring the impact of tactics on the stability of inter-related quality attributes during run-time. In this paper, we introduce a Markovian-based analytical model for dynamically assessing the impact of tactics on the stability behaviour of self-adaptive cloud architectures. The model also employs self-awareness capabilities for betterinforming the selection of optimal tactics configurations leading to stability. Experimental evaluations have shown the accuracy and efficiency of the model in measuring and predicting the impact of tactics on stabilising the Quality of Service provision and the adaptation process.

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PB - IEEE Computer Society Press

T2 - The 9th IEEE International Conference on Cloud Computing

Y2 - 27 June 2016 through 2 July 2016

ER -

Dynamic Modelling of Tactics Impact on the Stability of Self-aware Cloud Architectures

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