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Requirements-driven self-optimization of composite services using feedback control

Chen, Bihuan; Peng, Xin; Yu, Yijun and Zhao, Wenyun (2014). Requirements-driven self-optimization of composite services using feedback control. IEEE Transactions on Services Computing, 8(1) pp. 107–120.

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In an uncertain and changing environment, a composite service needs to continuously optimize its business process and service selection through runtime adaptation. To achieve the overall satisfaction of stakeholder requirements, quality tradeoffs are needed to adapt the composite service in response to the changing environments. Existing approaches on service selection and composition, however, are mostly based on quality preferences and business processes decisions made statically at the design time.

In this paper, we propose a requirements-driven self-optimization approach for composite services. It measures the quality of services (QoS), estimates the earned business value, and tunes the preference ranks through a feedback loop. The detection of unexpected earned business value triggers the proposed self-optimization process systematically. At the process level, a preference-based reasoner configures a requirements goal model according to the tuned preference ranks of QoS requirements, reconfiguring the business process according to its mappings from the goal configurations. At the service level, selection decisions are optimized by utilizing the tuned weights of QoS criteria.

We used an experimental study to evaluate the proposed approach. Results indicate that the new approach outperforms both fixed-weighted and floating-weighted service selection approaches with respect to earned business value and adaptation flexibility.

Item Type: Journal Item
Copyright Holders: 2013 IEEE
ISSN: 1939-1374
Project Funding Details:
Funded Project NameProject IDFunding Body
Adaptive Security and Privacy - Advanced Grant291652ERC
Keywords: quality of services (QoS); quality tradeoffs; self-optimization; business value; process reconfiguration; service selection
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 39225
Depositing User: Yijun Yu
Date Deposited: 18 Dec 2014 11:19
Last Modified: 07 Dec 2018 22:58
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