Title | ||
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Using enterprise architecture analysis and interview data to estimate service response time |
Abstract | ||
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Insights into service response time is important for service-oriented architectures and service management. However, directly measuring the service response time is not always feasible or can be very costly. This paper extends an analytical modeling method which uses enterprise architecture modeling to support the analysis. The extensions consist of (i) a formalization using the Hybrid Probabilistic Relational Model formalism, (ii) an implementation in an analysis tool for enterprise architecture and (iii) a data collection approach using expert assessments collected via interviews and questionnaires. The accuracy and cost effectiveness of the method was tested empirically by comparing it with direct performance measurements of five services of a geographical information system at a Swedish utility company. The tests indicate that the proposed method can be a viable option for rapid service response time estimates when a moderate accuracy within 15% is sufficient. |
Year | DOI | Venue |
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2013 | 10.1016/j.jsis.2012.10.002 | J. Strategic Inf. Sys. |
Keywords | Field | DocType |
moderate accuracy,analysis tool,interview data,rapid service response time,service response time,service management,enterprise architecture analysis,hybrid probabilistic relational model,analytical modeling method,service-oriented architecture,enterprise architecture,performance,information systems,quality of service | Service design,Service management,Enterprise architecture,Computer science,Knowledge management,Enterprise information system,Service level requirement,Enterprise integration,Enterprise information security architecture,View model,Marketing | Journal |
Volume | Issue | ISSN |
22 | 1 | 0963-8687 |
Citations | PageRank | References |
10 | 0.53 | 50 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Per Närman | 1 | 300 | 16.08 |
Hannes Holm | 2 | 191 | 14.59 |
Mathias Ekstedt | 3 | 634 | 49.70 |
Nicholas Honeth | 4 | 24 | 2.58 |