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Abstract. This paper presents a policy-supported architecture for adaptable service systems based on the combination of Reasoning Machines and Extended Finite State Machines. Policies are introduced to obtain flexibility with respect to specification and execution of adaptation mechanisms. The presented architecture covers two aspects: service system framework and adaptation mechanisms. The service system framework is a general framework for capability management. Adaptation mechanisms are needed for autonomous adaptation. The adaptation mechanisms can be based on static or dynamic policy systems. Capability management for of a simple music video-on demand service system with runtime simulation results based on the proposed architecture is presented.

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Adaptability is a property related to engineering as well as to the execution of networked service systems. This publication considers issues of adaptability both within a general and a scoped view. The general view considers issues of adaptation at two levels: 1) System of entities, functions and adaptability types, and 2) Architectures supporting adaptability. Adaptability types defined are capability-related, functionality-related and context-related adaptation. The scoped view of the publication is focusing on capability-related adaptation. A dynamic goal-based policy ontology is presented. The adaptation functionality is realized by the combination of Extended Finite State Machines, Reasoning Machines and Learning Mechanisms. An example case demonstrating the use of a dynamic goal-based policy is presented.

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