Monitoring and Information Alignment in Pursuit of an IoT-Enabled Self-Sustainable Interoperability

192 Pages·2017·7.3 MB·English

by  Filipe Correia

José Alexandre Pires Ferreira

Mestre em Engenharia Electrotécnica e de Computadores

Monitoring and Information Alignment in
Pursuit of an IoT-Enabled Self-Sustainable
Interoperability

Dissertação para obtenção do Grau de Doutor em
Engenharia Electrotécnica e de Computadores – Especialidade
em Sistemas de Informação Industriais

Orientador: Doutor Ricardo Luís Rosa Jardim Gonçalves,
Professor Auxiliar com Agregação, Faculdade de
Ciências e Tecnologia da Universidade Nova de
Lisboa
Co-orientador: Doutor Carlos Manuel Melo Agostinho, Professor
Auxiliar Convidado, Faculdade de Ciências e
Tecnologia da Universidade Nova de Lisboa

Júri:

Presidente: Prof. Doutor Jorge Joaquim Pamiés Teixeira
Arguentes: Prof. Doutor Raul Poler Escoto
Prof. Doutor João Pedro Mendonça de Assunção da Silva
Vogais: Prof. Doutor Jorge Joaquim Pamiés Teixeira
Prof. Doutor Ricardo Luís Rosa Jardim Gonçalves
Prof. Doutor Manuel Martins Barata
Prof. Doutor Carlos Eduardo Dias Coutinho
Prof Doutor José António Barata de Oliveira
Doutora Maria do Carmo Correia Marques

Dezembro 2017
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Copyright
Monitoring and Information Alignment in Pursuit of an IoT-Enabled Self-Sustainable
Interoperability
Copyright@ José Alexandre Pires Ferreira, Faculdade de Ciências e Tecnologias da
Universidade Nova de Lisboa
A Faculdade de Ciencias e Tecnologia e a Universidade Nova de Lisboa tem o direito,
perpétuo e sem limites geográficos, de arquivar e publicar esta dissertação através de exemplares
impressos reproduzidos em papel ou de forma digital, ou por qualquer outro meio conhecido ou que
venha a ser inventado, e de a divulgar através de repositórios científicos e de admitir a sua cópia e
distribuição com objectivos educacionais ou de investigacao, não comerciais, desde que seja dado
crédito ao autor e editor.

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To my family

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Acknowledgements
I would like to thank all the people who, in some way, supported me during the course of my
course and this dissertation.
First, my family, who never gave up on me during this phase of my life, who supported me all
those years and endured all the moments, lived during this doctorate.
To all my GRIS colleagues, especially to Carlos Agostinho, who helped me and believed me
at this moment, although it often seemed that I was not going to arrive, pushing me to do a better job
and successfully complete this dissertation.
My advisor, Dr. Ricardo Gonçalves for believing in my abilities and giving me his advice for the
successful completion of this work, and the great opportunity to work in GRIS.
For my great friends, Ana Mamede and Carla Mamede for always giving me support and
motivation to finally finish this dissertation, which gave me hope and believed in me all the time, made
me believe in myself, although I do not always show how much I appreciate to both of you. To
Catarina Ferreira, although we met a short time, you have been a good friend and helped me calm
down whenever I need so thanks to three.
For my special friends, who shared all the hard work during the course, this took many years,
but it was finally over. Thank you, Paulo Polaina, Francisco Cavaco and António Paulo, during all
these years together, vacations and the great nights we spent together.
Finally, for all Badjoras those in recent years were great fellowship at work, dinners, and
drinks, particularly André Coelho, Flávio Silva, João Lourenço, João Soares, João Ralo and Joaquim
Pereira. For Carlos Raposo, Fábio Lopes and João Soares for the support they gave in this work, they
were a great contribution and supported me to finish this dissertation.
The research leading to these results has received funding from the European Union Seventh
Framework Programme (FP7/2011-2014) under grant agreement n° 285132
(http://cordis.europa.eu/project/rcn/99927_en.html) and the European Union Horizon 2020 Programme
(H2020/2015-2017) under grant agreement nº 636909
(http://cordis.europa.eu/project/rcn/193440_en.html).
I would like to thank FCT – Foundation for Science and Technology funding through a Ph.D.
scholarship (SFRH/BD/84803/2012).

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Abstract
To remain competitive with big corporations, small and medium-sized enterprises (SMEs)
often need to be more dynamic, adapt to new business situations, react faster, and thereby survive in
today‘s global economy. To do so, SMEs normally seek to create consortiums, thus gaining access to
new and more opportunities. However, this strategy may also lead to complications. Due to the
different sources of enterprise models and semantics, organizations are experiencing difficulties in
seamlessly exchanging vital information via electronic means. In their attempt to address this issue,
most seek to achieve interoperability by establishing peer-to-peer mappings with different business
partners, or by using neutral data standards to regulate communications in optimized networks.
Moreover, systems are more and more dynamic, frequently changing to answer new customer‘s
requirements, causing new interoperability problems and a reduction of efficiency. Another situation
that is constantly changing is the devices used in the enterprises, as the Enterprise Information
Systems, devices are used to register internal data, and to be used to monitor several aspects. These
devices are constantly changing, following the evolution and growth of the market. So, it is important
to monitor these devices and doing a model representation of them. This dissertation proposes a self-
sustainable interoperable framework to monitor existing enterprise information systems and their
devices, monitor the device/enterprise network for changes and automatically detecting model
changes. With this, network harmonization disruptions are detected in a timely way, and possible
solutions are suggested to regain the interoperable status, thus enhancing robustness for reaching
sustainability of business networks along time.
Keywords
Self-Sustainable Interoperability; Model Morphisms; Multi-Agent Systems; Monitoring and
Assessment; Knowledge Management; Sensing Enterprise; Internet of Things.
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