Article

Toward an architectural knowledge base for wireless service engineering

VTT Tech. Res. Centre of Finland, Oulu, Finland
IEEE Transactions on Software Engineering (Impact Factor: 2.59). 06/2005; DOI: 10.1109/TSE.2005.60
Source: IEEE Xplore

ABSTRACT Wireless services are software-based services that exploit distribution infrastructure embedded in our everyday life as various communication and computing technologies. Service architecture defines concepts and principles to develop and maintain services to obtain the quality issues with minimum cost and faster time-to-market. In order to boost the development of wireless services, more effective means of using existing architectural know-how and artifacts are required. Our contribution is the architectural knowledge base that introduces three cornerstones: the service taxonomy, reference service architecture, and basic services that alt together provide an efficient means of creating added value with wireless services. The service taxonomy assists in identifying the required functional and quality properties of services and the constraints of the underlying technology platforms. The reference architecture realizes the required properties, based on a selected set of architectural styles and patterns, and provides a skeleton upon which a new end-user service can be developed faster and more easily by using partially ready-made solutions, and furthermore, to keep the architectural knowledge base evolving at the same time. The architectural knowledge base has been validated in several research projects with industrial companies.

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    ABSTRACT: There is growing recognition of the importance of documenting and managing background knowledge about architecture design decisions. However, there is little guidance on the types of information that form Ar- chitecture Design Knowledge (ADK), how to make implicitly described ADK explicit, and how such knowledge can be documented to improve ar- chitecture processes. We propose a framework that provides a support mechanism to capture and manage ADK. We analyze different approaches to capturing tacit and implicit design knowledge describe a process of ex- tracting ADK from patterns and an effective way of documenting it. We also present a data model to characterize architecture design primitives used or generated during architecture design and evaluation. This data model can be tailored to implement repositories of ADK. We complete this chapter with open issues that architecture research must confront in order to suc- cessfully transfer technology for capturing design rationale to the industry.

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