Title
Automated Discovery and Maintenance of Enterprise Topology Graphs
Abstract
Enterprise Topology Graphs (ETGs) represent a snapshot of the complete enterprise IT, including all its applications, processes, services, components, and their dependencies. In the past, ETGs have been applied in analysis, optimization, and adaptation of enterprise IT. But how to discover and maintain a complete, accurate, fresh, and fine-grained Enterprise Topology Graph? Existing approaches either do not provide enough technical details or do not cover the complete scope of Enterprise Topology Graphs. Although existing tools are able to discover valuable information, there is no means for seamless integration. This paper proposes a plug in-based approach and extensible framework for automated discovery and maintenance of Enterprise Topology Graphs. The approach is able to integrate various kinds of tools and techniques into a unified model. We implemented the proposed approach in a prototype and applied it to different scenarios. Due to the vital role of discovery plugins in our approach, we support plug in development with a systematic testing method and discuss the lessons we learned. The results presented in this paper enable new ways of enterprise IT optimization, analysis, and adaptation. Furthermore, they unlock the full potential of past research, which previously required manual modeling of ETGs.
Year
DOI
Venue
2013
10.1109/SOCA.2013.29
SOCA
Keywords
Field
DocType
discovery plugins,automated discovery,plug in-based approach,complete enterprise,enterprise it optimization,past research,fine-grained enterprise topology graph,enterprise topology graphs,complete scope,graph theory,software architecture
Architecture domain,Graph theory,Data mining,Topology,Integrated enterprise modeling,Computer science,Server,Enterprise information system,Plug-in,Software architecture,Maintenance engineering
Conference
Citations 
PageRank 
References 
5
0.43
18
Authors
4
Name
Order
Citations
PageRank
Tobias Binz151246.31
Uwe Breitenbücher256672.64
Oliver Kopp370859.24
Frank Leymann46482578.87