At DISP Lab, at Lyon, France, there is a PhD opening on « Ensuring Interoperability for “smart” information systems”. More information below.

What is important is that all the development will be done using Pharo/
Moose.

If you are interested, please contact Jannik Laval <jannik.laval@gmail.com> 

=====
Ph.D. thesis (CIFRE)
Berger Levrault and DISP Lab, Lyon, France

Title: Ensuring Interoperability for “smart” information systems

Enterprise: Berger Levrault
Research Laboratory: DISP Lab
Where: Lyon, France
Recruitment date: As soon as possible
Application deadline: As soon as possible
Function: 3 years PhD candidate position in Berger Levrault (CDI). The
position will be part time between Berger Levrault and DISP Lab.
Research topic : data interoperability, application exchange protocols,
service-oriented architecture, event architecture, semantics, monitoring.

Context:

The need for sharing, exchanging and promoting information from information
systems is constantly increasing and now represents a major concern in the
various reforms of the local public sector (consolidation of local
authorities, implementation of in place in 2016 Hospital Group Territory,
Digital Republic). It is therefore essential to design “platforms” capable
of providing answers to the rationalisation and simplification of data
exchanges between software applications and with the outside world to
promote and simplify the application of all these reforms.

In addition, service-oriented architectures and event architectures (SOA,
EDA) are mature and widely used. At Berger-Levrault, their implementation
ensures the scalability and maintainability of solutions. These
architectures are characterised by the flexibility and the loose coupling
of the subsystems that compose them (ie services, applications, IS …) and
rely on several means (Hohpe & Woolf, 2004) to route the data within this
network of systems communicating. At this stage of maturity, we observe
that these data exchanges are operational and meet the requirements of
interoperability between heterogeneous systems (Leal, 2019).

Nevertheless, the number of standards recognised and used by the French
public sector, the privileged sector of Berger-Levrault, increases the
level of interconnection difficulties (Kurniawan & Ashari, 2015) of the
different solutions developed by Berger-Levrault. This is all the more
remarkable when it comes to communicating with external solutions or
platforms (partners and / or competitors). This multiplicity of exchanges
and types of exchanges generates a great deal of complexity and highlights
the need to master the exchange system as effectively as possible. Berger
Levraut today lacks visibility on existing exchanges and mechanisms to
evaluate them (Leal, Guédria, & Panetto, 2019) which complicates the
detection of dysfunctions and the discovery of their origins.

Moreover, it is essential for the Berger-Levrault applications to be able
to adapt to the new rules and standards while continuing to integrate the
dematerialization of the public service. The evolution of these modalities
has an almost systematic impact on the exchange of data put in place to
ensure interoperability. Hence the need to build flexible and scalable
exchange architectures and to follow the evolution of these exchanges.

These transformations imply a large volume of data exchanged and subject to
variations that can be strong during periods of “high attendance” such as
elections by electronic vote. The very nature of exchanges can be affected
especially with the multiplicity of connected objects (Buyya & Dastjerdi,
2016). These are increasingly used by public institutions for the benefit
of the management of city facilities or user services. The increase in
volumes of data exchanged therefore implies the implementation of exchange
architectures that are able to support the load but also the great
variability of the types and frequencies of data production. This requires
distributed architectures (in infrastructure and flow), adaptable or even
self-adaptable (Gascon-Samson et al 2015) to promote the system’s
resistance to faults while avoiding potential congestion phenomena.

Based on this reflection, a research project was conducted in partnership
by Berger-Levrault and the DISP laboratory (Amokrane et al., 2018). These
early works have identified a set of scientific and technical barriers:
• Lack of visibility on existing interoperability exchanges. Indeed, the
current exchanges are not traced and the existing monitoring mechanisms
focus mainly on low level information, such as the performance of the
infrastructure or the use of the memory, without correlation with business
information. In addition, few methods for evaluating interoperability are
concerned with the effective evaluation (a posteriori of the
implementation) of the interoperability of the data, and few of them are
tooled (Leal, Guédria, & Panetto, 2019).
• The complexity of trade maintenance. This is due to the lack of
traceability of the exchanges, on the one hand, and that of the evolution
of the exchange architecture configurations on the other hand. This
complicates the identification of failures or dysfunctions and the analysis
of their causes, and poses difficulties for the setting up of mechanisms of
alerts or significant notifications. In addition, the lack of
capitalisation of information relating to trade does not allow to consider
a forecast maintenance.
• The development of the different modules of the exchange system is manual
and the remediation of malfunctions is done in an ad hoc manner. In
addition to the cost of development and correction that this implies, this
does not meet the responsiveness requirements of some business areas. Hence
the need to build adaptable exchange systems using dynamic interoperability
hubs (Agostinho, et al., 2016).

The objective of this thesis proposal is to produce an approach to the
implementation cycle of application exchanges, from design to maintenance,
which will enhance the reliability and resilience of the interoperability
exchange system. The solution will ultimately orchestrate all the
application and service exchanges to ensure optimisation of the use of
software and infrastructure resources of public institutions.

To meet the needs in terms of interoperability, the work to be carried out
is articulated in two axes that we structure as follows:
– A flexible architecture for the implementation of interoperability. Here
we consider the basic functionalities reflecting the activities necessary
for the establishment of the means of interoperability.
– A reflexive architecture for managing interoperability at a meta-level.
This axis relates to setting up means of administration, monitoring and
maintenance of the exchange network set up for interoperability.
The work must also incorporate the concepts of security, scalability and
usability. Requirements to be met when developing any solution to lift the
locks and meet the objectives of this thesis work.

—–
Agostinho, C., Ducq, Y., Zacharewicz, G., Sarraipa, J., Lampathaki, F.,
Poler, R., & Jardim-Goncalves, R. (2016). Towards a sustainable
interoperability in networked enterprise information systems: Trends of
knowledge and model-driven technology. Computers in Industry, 79, 64 – 76.
doi:10.1016/j.compind.2015.07.001
Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., & Merle, P. (2017). Elasticity
in cloud computing: state of the art and research challenges. IEEE
Transactions on Services Computing, (pp. 430-447).
Amokrane, N., Laval, J., Lanco, P., Derras, M., & Moalla, N. (2018).
Analysis of Data Exchanges, Contribution to Data Interoperability
Assessment. 9th international Conference on Intelligent Systems 2018.
Madeira, Portugal.
Andary, J. F., & Sage, A. P. (2010). The role of service oriented
architectures in systems engineering. Information Knowledge Systems
Management, 9(1), 47-74.
Belfadel, A., Laval, J., Cherifi, C., & Moalla, N. (2018). Towards service
orchestration through software capability profile. I-ESA Interoperability
for Enterprise Systems and Applications 2018. Berlin, Germany.
Bernus, P., Goranson, T., Gøtze, J., Jensen-Waud, A., Kandjani, H., Molina,
A., . . . Turner, P. (2016). Enterprise engineering and management at the
crossroads. Computers in Industry, 79, 87 – 102. doi:10.1016/
j.compind.2015.07.010
Buyya, R., & Dastjerdi, A. V. (2016). Internet of Things: Principles and
paradigms. Elsevier.
Cabot, J., Clarisó, R., Brambilla, M., & Gérard, S. (2017). Cognifying
model-driven software engineering. Federation of International Conferences
on Software Technologies: Applications and Foundations (pp. pp. 154-160).
Springer.
Chappell, D. (2004). Enterprise Service Bus. : O’Reilly Media, Inc.
Cheung, A. K., & Jacobsen, H. A. (2010). Load balancing content-based
publish/subscribe systems. ACM Transactions on Computer Systems (TOCS).
Chhun, S., Moalla, N., & Ouzrout, Y. (2016). QoS ontology for service
selection and reuse. Journal of Intelligent Manufacturing, 27(1), 187-199.
Crosby, M., Pattanayak, P., Verma, S., & Kalyanaraman, V. (2016).
Blockchain technology: Beyond bitcoin. Applied Innovation, 2(6-10).
Curry, E. (2004). Message-oriented middleware, Middleware for
communications,.
Czarnecki, K., Eisenecker, U., Glück, R., Vandevoorde, D., & Veldhuizen, T.
(2000). Generative programming and active libraries. Generic Programming
(pp. pp. 25-39). Berlin, Heidelberg.: Springer.
Erl, T. (2005). Service-oriented architecture: concepts, technology, and
design. Prentice Hall Professional Technical Reference.
Fahad, M., Moalla, N., & Bouras, A. (2012). Detection and resolution of
semantic inconsistency and redundancy in an automatic ontology merging
system. Journal of Intelligent Information Systems, 39(2), 535-557.
Fahad, M., Moalla, N., Bouras, A., Abdul Qadir, M., & Farukh, M. (2011).
Towards Classification of Web Ontologies for the Emerging Semantic Web.
Journal of Universal Computer Science, 17(7), 1021-1042.
Fülöp, L. J., Tóth, G., Rácz, R., Pánczél, J., Gergely, T., Beszédes, A., &
Farkas, L. (2010). Survey on complex event processing and predictive
analytics. the Fifth Balkan Conference in Informatics, (pp. pp. 26-31).
Gascon-Samson, J., Garcia, F. P., Kemme, B., & Kienzle, J. (2015).
Dynamoth: A scalable pub/sub middleware for latency-constrained
applications in the cloud. In 2015 IEEE 35th International Conference on
Distributed Computing Systems , (pp. pp. 486-496).
Gokhale, A., Schmidt, D. C., Natarajan, B., & Wang, N. (2002). Applying
model-integrated computing to component middleware and enterprise
applications. Communications of the ACM, (pp. 65-70).
Hachicha, M., Moalla, N., Fahad, M., & Ouzrout, Y. (2015). Performance
assessment architecture for collaborative business processes in BPM-SOA
based environments. International journal of Data & Knowledge Engineering,
105, 73-89.
Hohpe, G., & Woolf, B. (2004). Enterprise integration patterns:
Designing,building, and deploying messaging solutions. Addison-Wesley
Professional.
Khare, S., Sun, H., Zhang, K., Gascon-Samson, J., Gokhale, A., Koutsoukos,
X., & Abdelaziz, H. (2018). Scalable edge computing for low latency data
dissemination in topic-based publish/subscribe. In 2018 IEEE/ACM Symposium
on Edge Computing (SEC) (pp. pp. 214-227). IEEE.
Kurniawan, K., & Ashari, A. (2015). Service orchestration using enterprise
service bus for real-time government executive dashboard system. 2015
International Conference on Data and Software Engineering (ICoDSE), (pp.
207-212). Yogyakarta. doi:10.1109/ICODSE.2015.7436999
Laval, J., Cherifi, C., & Cheutet, V. (2018). Towards the measurement of
Enterprise Information Systems agility to support EIS improving projects.
International Journal of Agile Systems and Management, 11(3):222–246.
Leal, G. D. (2019). Support à la décision pour l’analyse de
l’interopérabilité des systèmes dans un contexte d’entreprises en réseau.
(Doctoral dissertation, Université de Lorraine).
Leal, G., Guédria, W., & Panetto, H. (2019). Interoperability Assessment: A
Systematic Literature Review. Computers in Industry (In Press).
Luckham, D. C. (2011). Event processing for business: organizing the
real-time enterprise. John Wiley & Sons.
Mallek, S. (2012). Contribution au développement de l’interopérabilité en
entreprise : vers une approche anticipative de détection de problèmes
d’interopérabilité dans des processus collaboratifs.
Object Management Group. (2006). Méta Object Facility (MOF) 2.0 Core
Specification.
Panettoa, H., Zdravkovicc, M., Jardim-Goncalvesd, R., Romeroe, D., Cecilg,
J., & Mezgárh, I. (2016). New perspective for the future interoperable
enterprise systems. Computers in Industry, s.l. : Elsevier, 79, 47-63.
doi:10.1016/j.compind.2015.08.001
WSO2. (2015). The Evolution of Integration: A Comprehensive Platform for a
Connected Business. White Paper. Récupéré sur http://wso2.com/

—
~~Jannik Laval~~
Enseignant-chercheur
Responsable Pédagogique Licence Coordonnateur de Projet
IUT Lumière, Université Lumière Lyon 2
laboratoire DISP
+33 4 78 77 43 06
http://www.jannik-laval.eu
http://www.phratch.com
http://www.approchealpes.info