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Self-adaptation through incremental generative model transformations at runtime

Chen, Bihuan; Peng, Xin; Yu, Yijun; Nuseibeh, Bashar and Zhao, Wenyun (2014). Self-adaptation through incremental generative model transformations at runtime. In: 36th International Conference on Software Engineering, Hyderabad, ACM/IEEE.

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Abstract

A self-adaptive system uses runtime models to adapt its architecture to the changing requirements and contexts. However, there is no one-to-one mapping between the requirements in the problem space and the architectural elements in the solution space. Instead, one refined requirement may crosscut multiple architectural elements, and its realization involves complex behavioral or structural interactions manifested as architectural design decisions. In this paper we propose to combine two kinds of self-adaptations: requirements-driven self-adaptation, which captures requirements as goal models to reason about the best plan within the problem space, and architecture-based self-adaptation, which captures architectural design decisions as decision trees to search for the best design for the desired requirements within the contextualized solution space. Following these adaptations, component-based architecture models are reconfigured using incremental and generative model transformations. Compared with requirements-driven or architecture-based approaches, the case study using an online shopping benchmark shows promise that our approach can further improve the effectiveness of adaptation (e.g. system throughput in this case study) and offer more adaptation flexibility.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 ACM
ISBN: 1-4503-2756-7, 978-1-4503-2756-5
Project Funding Details:
Funded Project NameProject IDFunding Body
Adaptive Security And Privacy (ASAP)291652ERC
Science Foundation Ireland Grant10/CE/I1855SFI
Keywords: self-adaptation; twin-peaks; requirements; architecture; generative transformations; SEAD; ASAP
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Policing Research and Learning (CPRL)
Centre for Research in Computing (CRC)
International Development & Inclusive Innovation
Related URLs:
Item ID: 39627
Depositing User: Yijun Yu
Date Deposited: 03 Mar 2014 10:02
Last Modified: 10 Feb 2017 03:57
URI: http://oro.open.ac.uk/id/eprint/39627
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