Enterprise Architecture: A Framework Supporting System Quality Analysis

Abstract:

Enterprise Architecture is a model-based approach to business-oriented IT management. To promote good IT decision making, an enterprise architecture framework needs to explicate what kind of analyses it supports. Since creating enterprise architecture models is expensive and without intrinsic value, it is desirable to only create enterprise architecture models based on meta-models that support well-defined analyses. This paper suggests a meta-model derived specifically with a set of theory-based system quality analyses in mind. The ISO 9126-based theory behind the system quality analysis is introduced in the shape of an extended influence diagram. Finally, an example illustrates that our theory-based meta-model does support system quality analysis.

Introduction:

Enterprise architecture is an approach to enterprise information systems management that relies on models of the information systems and their environment. The main idea is very old. Instead of building the enterprise information system using trial and error, a set of models is proposed to predict the behaviour and effects of changes to the system. The enterprise architecture models allow reasoning about the consequences of various scenarios and thereby support decision making. A number of enterprise architecture initiatives have been proposed, including The Open Group Architecture Framework (TOGAF) [2], the Zachman Framework [3], GERAM [4], CIMOSA [5], PERA [6], DoDAF [1], Intelligrid [7] and more.

In order to predict whether enterprise architecture scenario A or B is preferable, three things are needed. Firstly, models over the two scenarios need to be created. Secondly, it is necessary to define what is desirable; the goals. If two scenarios offer the same functionality, do we want the systems to provide high service availability or is system modifiability more important? Is it more important with high system performance than high information security or maintainability? Thirdly, we need to understand the causal chains from scenario choice to goals. Scenario A features hardware redundancy that positively affects the system reliability which in turn improves the service availability. However, scenario B is built on a loosely coupled technology, which promotes the modifiability of the system.

In order to perform these kinds of analyses, the enterprise architecture models need to contain the proper information. In the above example, where the decision maker is interested in service availability and system modifiability, the models need to answer questions regarding hardware redundancy and component coupling, for instance. The kind of information contained in a model is given by its meta-model, so it is important that enterprise architecture meta-models are properly designed.

In order to determine if a meta-model is amenable to the analysis of a certain quality attribute, e.g. information security or interoperability, it would be helpful with a structured account of that analysis. We will use a notation called extended influence diagram (EID) in order to formalise the analyses of various quality attributes. [13]

Figure 1 depicts the relation between an enterprise architecture scenario, modelled using a meta-model, the analysis of the scenario, the formal specification of the analysis through an extended influence diagram and finally the output: the quality to be analysed.

System Quality Attributes:

Maintainability Analysis Influence Diagram:

Information System Security Analysis Influence Diagram:

PERDAF Enterprise Architecture Meta-model:

Purpose-Oriented EnterpRise System Decision-Making Architecture Framework (PERDAF):

System Quality Attribute Model:

Conclusion:

his paper has presented the PERDAF enterprise architecture meta-model supporting enterprise system quality analysis. The meta-model consists of classes with accompanying attributes that can be used to create enterprise architecture models from which it is possible to extract precisely the information that is needed for quantitative system quality analysis.

Furthermore, this paper presented a system quality analysis framework in the form of an extended influence diagrams. The use of the meta-model and the extended influence diagram was further demonstrated in an example.