DocumentCode
2721429
Title
A Network Topology Clustering Algorithm for Service Identification
Author
Guan, Qingbo ; Feng, Shuxing ; Ma, Yanhua
Author_Institution
Dept. of Test & Command, Acad. of Equip., Beijing, China
fYear
2012
fDate
11-13 Aug. 2012
Firstpage
1583
Lastpage
1586
Abstract
One of the key activities in service-oriented solution development is the identification of services according to a set of predefined design principles. Existing Top-Down technique is normal way for service identification and some relative further research are based on it. They all paid more attention to how to automatic decompose business and take bottom/leaf actives as a candidate service while ignore service character, such as loose couple and high cohesive. The purpose of this paper is to provide a way to optimize business process for Service Identification. The study was composed of four majors parts: (1) a directed graph model is built to describe business process simply by employing Graph Theory, (2) a five steps identification produce is given and some formulas are present to, (3) Based on DBSCAN (Density-Based Spatial Clustering of Applications with Noise), a network topology Clustering algorithm was given and (4) an example has been conducted to show the applicability.
Keywords
business data processing; directed graphs; optimisation; pattern clustering; service-oriented architecture; DBSCAN; automatic business decomposition; business process optimization; density-based spatial clustering of applications with noise; directed graph model; graph theory; network topology clustering algorithm; service identification; service-oriented solution development; top-down technique; Analytical models; Business; Clustering algorithms; Couplings; Graph theory; Network topology; Topology; DBSCAN; business process; directed graph model; network topology clustering algorithm; service identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-0721-5
Type
conf
DOI
10.1109/CSSS.2012.396
Filename
6394635
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