DocumentCode
125499
Title
RESTful Web Service Mining: Simple Algorithm Supporting Resource-Oriented Systems
Author
Stroinski, Andrzej ; Dwornikowski, Dariusz ; Brzezinski, Jerzy
Author_Institution
Inst. of Comput. Sci., Poznan Univ. of Technol., Poznań, Poland
fYear
2014
fDate
June 27 2014-July 2 2014
Firstpage
694
Lastpage
695
Abstract
Composition of Web Services (WS) into business processes (BP) often results in occurrence of defects in a process: implicit dependencies, incorrect contexts, non-optimal or bottlenecked workflow, and deadlocks. To deal with these problems, WS Mining (process mining in SOA) research provides methods and tools to discover, evaluate and enhance real world processes basing on a process model discovered from a log. Unfortunately, current research in this field only concerns SOAP-WS which are not as well-suited as RESTful-WS in the context of current research trends like Internet of Things or Web 2.0. WS Mining methods and tools should consider RESTful-WS where functionality of the system is expressed in the form of resources and relationships among them. In this paper we show the idea of discovering process models for interacting RESTful-WS with respect to both workflow and resources perspectives. We introduce extended version of the α algorithm (AA), RESTful-WS mining algorithm (RMA), which discovers hierarchical process models and resource-oriented perspective of a process including local and global behavior. Finally, we present a brief discussion on how RMA decomposes a problem into smaller ones, significantly reducing the execution time in real time scenarios.
Keywords
Web services; data mining; service-oriented architecture; Internet of Things; RESTful Web service mining; SOA; SOAP-WS; WS mining; Web 2.0; Web service composition; business process; hierarchical process models; process mining; resource-oriented perspective; resource-oriented systems; service oriented architecture; Abstracts; Context; Context modeling; Data mining; Educational institutions; Service-oriented architecture; Process Mining; RESTful Web Service Mining; RESTful Web Services;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Services (ICWS), 2014 IEEE International Conference on
Conference_Location
Anchorage, AK
Print_ISBN
978-1-4799-5053-9
Type
conf
DOI
10.1109/ICWS.2014.106
Filename
6928966
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