Start Date

12-13-2015

Description

The principle of modularity has been increasingly applied to services in recent years as service providers seek to reduce time and cost of delivering customized services. Numerous methods have been proposed and applied to services to design modular service architectures. However, these methods are insufficient for specific requirements of service modularization, such as the gradual refinement of the underlying complex service system or the integration of experts from different domains. Therefore, we propose a framework for service modularization that covers the phases of analysis, module and architecture design, implementation, and monitoring of a modular service architecture. This framework builds on a series of demonstrations in a complex service system and allows for a systematization of the required tasks, the refinement of gathered data, a structured exchange of information between all phases by the help of the Multiple Domain Matrix Method, and the integration of experts from different domains.

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Dec 13th, 12:00 AM

FAMouS – Framework for Architecting Modular Services

The principle of modularity has been increasingly applied to services in recent years as service providers seek to reduce time and cost of delivering customized services. Numerous methods have been proposed and applied to services to design modular service architectures. However, these methods are insufficient for specific requirements of service modularization, such as the gradual refinement of the underlying complex service system or the integration of experts from different domains. Therefore, we propose a framework for service modularization that covers the phases of analysis, module and architecture design, implementation, and monitoring of a modular service architecture. This framework builds on a series of demonstrations in a complex service system and allows for a systematization of the required tasks, the refinement of gathered data, a structured exchange of information between all phases by the help of the Multiple Domain Matrix Method, and the integration of experts from different domains.