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Authors: Rafael Z. Frantz 1 ; Sandro Sawicki 1 ; Fabricia Roos-Frantz 1 ; Iryna Yevseyeva 2 and Michael Emmerich 3

Affiliations: 1 Unijuí University, Brazil ; 2 Newcastle University, United Kingdom ; 3 Leiden University, Netherlands

ISBN: 978-989-758-097-0

Keyword(s): Simulation, Enterprise Application Integration, Domain-Specific Language, Markov Decision Process.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Coupling and Integrating Heterogeneous Data Sources ; Databases and Information Systems Integration ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Methodologies and Technologies ; Modeling of Distributed Systems ; Operational Research ; Simulation

Abstract: The software ecosystem of an enterprise is usually composed of an heterogeneous set of applications, databases, documents, spreadsheets, and so on. Such resources are involved in the enterprise’s daily activities by supporting its business processes. As a consequence of market change and the enterprise evolution, new business processes emerge and the current ones have to be evolved to tackle the new requirements. It is not a surprise that different resources may be required to collaborate in a business process. However, most of these resources were devised without taking into account their integration with the others, i.e., they represent isolated islands of data and functionality. Thus, the goal of an integration solution is to enable the collaboration of different resources without changing them or increasing their coupling. The analysis of integration solutions to predict their behaviour and find possible performance bottlenecks is an important activity that contributes to increase the quality of the delivered solutions. Software engineers usually follow an approach that requires the construction of the integration solution, the execution of the actual integration solution, and the collection of data from this execution in order to analyse and predict their behaviour. This is a costly, risky, and time-consuming approach. This paper discusses the usage of Markov models for formal modelling of integration solutions aiming at enabling the simulation of the conceptual models of integration solutions still in the design phase. By using well-established simulation techniques and tools at an early development stage, this new approach contributes to reduce cost, risk, development time and improve software quality attributes such as robustness, scalability, and maintenance. (More)

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Paper citation in several formats:
Z. Frantz, R.; Z. Frantz, R.; Sawicki, S.; Roos-Frantz, F.; Yevseyeva, I. and Emmerich, M. (2015). On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-097-0, pages 260-267. DOI: 10.5220/0005346902600267

@conference{iceis15,
author={Rafael Z. Frantz. and Rafael Z. Frantz. and Sandro Sawicki. and Fabricia Roos{-}Frantz. and Iryna Yevseyeva. and Michael Emmerich.},
title={On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2015},
pages={260-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005346902600267},
isbn={978-989-758-097-0},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems
SN - 978-989-758-097-0
AU - Z. Frantz, R.
AU - Z. Frantz, R.
AU - Sawicki, S.
AU - Roos-Frantz, F.
AU - Yevseyeva, I.
AU - Emmerich, M.
PY - 2015
SP - 260
EP - 267
DO - 10.5220/0005346902600267

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