The International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC 2020)
Conference Date: September 15-17, 2020
  • IIoTBDSC 2020
Keynote & Invited Speakers

Keynote Speakers 

Prof. Dr. Peter KACSUK

SZTAKI and Univ. of Westminster

The power of cloud orchestration


Cloud systems have been proven to be very useful to create complex digital services by deploying and connecting the required services in the cloud according to predefined descriptors. Meanwhile the creation of such descriptors requires deep cloud expertise, their usage requires only minimal cloud knowledge so even end-users with little cloud experience can apply them. Hence 1st generation cloud orchestrators (Terraform, Juju, Heat, Occopus, etc.) assisted the creation of such complex systems by significantly simplifying the deployment and configuration process of the component services. Beyond that they enabled the creation of reference architectures that play a particularly important role in Big data and AI applications. Another typical type of complex services are the data processing pipelines implemented as data workflows. In the first part of the talk we take a journey in the world of reference architectures and data pipelines and show how cloud orchestrators can help everyday work of system engineers and advance users to create such services in even heterogeneous, hybrid cloud systems.

Beyond the initial deployment of virtual machines and containers, second generation cloud orchestrators enable the dynamic scaling (up and down) of created complex digital services that makes these services much more efficient and economic in terms of always applying the optimal number of virtual machines and containers required by predefined conditions of running these services. Such a second-generation cloud orchestrator, called MiCADO was developed in the EU project COLA (Cloud Orchestration at the Level of Applications) and its power was demonstrated in several commercial application areas. One of them is evacuation modelling that was developed by Saker Solutions Ltd. and extended with the use of MiCADO. In the second part of the talk the concept and architecture of MiCADO will be explained and its usage in evacuation modelling will be described. Finally, some further plans of using and further extending MiCADO in the framework of the newly started EU project DigitBrain will be presented.


Prof. Dr. Peter KACSUK is the Head of the Research Laboratory of the Parallel and Distributed Systems. He received his MSc and university doctorate degrees from the Technical University of Budapest in 1976 and 1984, respectively. He received the kandidat degree from the Hungarian Academy of Sciences in 1989. He habilitated at the University of Vienna in 1997. He received his professor title from the Hungarian President in 1999 and the Doctor of Academy degree (DSc) from the Hungarian Academy of Sciences in 2001. He has been a part-time full professor at the Cavendish School of Computer Science of the University of Westminster in London and at the Eötvös L¨®r¨¢nd University of Science in Budapest since 2001. He served as visiting scientist or professor several times at various universities of Austria, England, Germany, Spain, Australia and Japan. He has published two books, two lecture notes and more than 200 scientific papers on parallel computer architectures, parallel software engineering and Grid computing. He is co-editor-in-chief of the Journal of Grid Computing published by Springer.

Prof. Witold Pedrycz

University of Alberta, Canada

Interpretability in Data Analytics with Information Granules


One of the ongoing timely quests in data analytics is about interpretability of results. The problem is multifaceted as it engages various ways of characterization of the findings. We demonstrate that interpretability comes hand in hand with several key features including a level of abstraction of the findings, their stability and efficient ways of accommodation of domain knowledge so that it could be used as a sound guiding vehicle of user-centric knowledge discovery. We offer a formal formulation of the problem, propose some performance indexes and show interrelationships among the features identified above. We advocate that information granules supported by Granular Computing deliver a comprehensive conceptual and algorithmic processing environment. As clustering has been one among central conceptual pursuits of data analytics, we cast a general discussion with a close association with clusters and their interpretation. The general scheme composed of a series of phases: data¡ªclusters¡ªinformation granules-linguistic summarization is discussed vis-¨¤-vis successive levels of abstraction arising in the consecutive steps. We move beyond data-focused clustering mechanisms by bringing mechanisms of knowledge-oriented clustering where data intensive clustering is seamlessly combined with crucial pieces of domain knowledge. A class of reference-driven clustering algorithms is developed in which key results are expressed and quantified in terms of semantically sound and user -supplied landmarks.  


Witold Pedrycz (F¡¯98) received the M.Sc., Ph.D., and D.Sci. degrees from the Silesian University of Technology, Gliwice, Poland.,He is currently a Professor and the Canada Research Chair in computational intelligence with the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada. He is also with the System Research Institute, Polish Academy of Sciences, Warsaw, Poland, where he is also a Foreign Member. He has authored 15 research monographs covering various aspects of computational intelligence, data mining, and software engineering. His current research interests include the computational intelligence, fuzzy modeling, granular computing, knowledge discovery and data mining, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and software engineering. Dr. Pedrycz currently serves as a member for a number of editorial boards of other international journals. He is a Fellow of the Royal Society of Canada. He was a recipient of the IEEE Canada Computer Engineering Medal, the Cajastur Prize for Soft Computing from the European Center for Soft Computing, the Killam Prize, and the Fuzzy Pioneer Award from the IEEE Computational Intelligence Society. He is intensively involved in editorial activities. He is an Editor-in-Chief of Information Science, and Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley) and the International Journal of Granular Computing (Springer).

Invited Speakers 

Dr Muthu Ramachandran

Leeds Beckett University, UK

Software Engineering Framework for IoT-Fog-Edge-CloudComputing (SEF-IFEC 2020)


IoT, Fog, Edge, and Cloud (IFEC) paradigm have emerged to address the need for more efficient integration of large scale real-time data streaming applications with widespread growth in IoT devices with 5G connected devices seamlessly. Besides, IFEC systems also needed to efficient control of trust, security & privacy (TSP) in the current pandemic of COVID-19 with multitude of devices and people connected with apps for predicting people to people. In addition, in recent years, we experienced lack of security concerns with smart home IoT applications such as home security cameras, etc. (Varghese & Hayajneh, 2018), (Hu, Yang, Lin, & Wang, 2020), & (Yassein, Hmeidi, Shatnawi, Mardini, & Khamayseh, 2019). Therefore, this talkproposes a systematic software engineering framework for IFEC applications which allow us to manage, maintain, and reuse on-the-fly. The tech analyst company IDC predicts there will be 50 billion connected IoT devices by 2025 (IDC 2019). Therefore, IFEC applications will generate and consume trillions of data volume and complex data traffic. Hence, this talk proposes a comprehensive requirements engineering framework for IFEC applications which can also be specified using BPMN modelling and simulation to verify and validate IFEC requirements with smart contracts using blockchain technology to Build Trust, Security, and Privacy In (BTSPI). Our initial design of IFEC architecture design and the simulation results fora large scale data streaming application shows the complexity and resource constraints needed before design and implementation which can save cost and improve process and quality of the IFEC applications. 


Dr Muthu Ramachandran is a Principle Lecturer (Associate Professor) at the School of Built Environment, Engineering and Computing at Leeds Beckett University, UK. Muthu has extensive research experience coupled with a teaching background and experiences on software and systems engineering methods & lifecycle, software development, agile software engineering, project management skills, process improvement skills, internet technology, mobile, networks, and distributed computing, real-time & embedded systems, cloud computing, service-oriented architecture, and IT systems development for the past 25 years. He was as a research scientist at India Space Research Labs where he worked on real-time systems development projects. Muthu is an author of two books: Software Components: Guidelines and Applications (Nova Publishers, NY, USA, 2008) and Software Security Engineering: Design and Applications (Nova Publishers, NY, USA, 2011). He is also an edited co-author of a book, Handbook of Research in Software Engineering (IGI, 2010) and has edited the book KE for SDLC (2011). He has widely authored published journal articles, book chapters and conferences materials on various advanced topics in software engineering and education. He received his Master's from the Indian Institute of Technology, Madras and from Madurai Kamaraj University, Madurai, India. He is a member of various professional organizations and computer societies: IEEE, ACM, Fellow of BCS, and Fellow of HEA. He was a speaker to the 5th international symposium on SOA Cloud 2012, London, COMPLEXIS 2016 and FEMIB 2019.

© 2020 The International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC 2020)