Keynotes

ICNet-2022 - Keynotes

1. Thomas C. Schmidt

Thomas C. Schmidt is professor of Computer Networks and Internet Technologies at Hamburg University of Applied Sciences, where he heads the Internet Technologies research group (iNET). Prior to moving to Hamburg, he was director of a scientific computer centre in Berlin. He studied mathematics, physics and German literature at Freie Universitaet Berlin and University of Maryland, and received his Ph.D. from FU Berlin in 1993. Since then he has continuously conducted numerous national and international research projects. He was the principal investigator in a number of EU, nationally funded and industrial projects as well as visiting professor at the University of Reading, U.K.. His continued interests lie in the development, measurement, and analysis of large-scale distributed systems like the Internet. He serves as co-editor and technical expert in many occasions and is actively involved in the work of IETF and IRTF. Together with his group he pioneered work on an information-centric Industrial IoT and the emerging data-centric Web of Things. Thomas is a co-founder of several large open source projects and coordinator of the community developing the RIOT operating system - the friendly OS for the Internet of Things.

Talk Title: The Data-centric Web of Things: From Network Research to Standardized Networking

Talk Abstract

About 20 years ago, research started to explore network architectures and protocols that better cater to constrained wireless communication than plain TCP/IP. The major objectives were to ease access to data in the Internet of Things (IoT) while increasing reliability and lowering the overall end-to-end delay. Research consolidated with the proposal of a new, data-centric networking paradigm coined Information Centric Networking (ICN). ICN integrated four new networking functions – (i) named access to data, (ii) hop-wise data transfer, (iii) in-network caching, and (iv) content object security -- in a clean slate network architecture and protocols such as Named Data Networking (NDN). Extensive studies revealed various performance benefits of ICN, but deployment remained hesitant as it is incompatible with IP. Recently, the IETF CoRE working group started to standardize CoAP extension that enable the four networking functions of ICN and resolve this incompatibility.

In this talk, we revisit the ICN networking principles and derive the Data-centric Web of Things architecture based on restful CoAP interactions. We introduce its implementation on the RIOT operating system and highlight insights, which we gained from extensive networking experiments.

2. Mauro Tortonesi

Mauro Tortonesi is an Associate Professor with the Department of Mathematics and Computer Science, University of Ferrara, Italy. He received the Ph.D. degree in computer engineering from the University of Ferrara in 2006. He was a Visiting Scientist with the Florida Institute for Human & Machine Cognition (IHMC), Pensacola, FL, USA, from 2004 to 2005 and with the United States Army Research Laboratory, Adelphi, MD, USA, in 2015.

He has an extensive research experience in Industry 4.0, acquired within many collaborations with world leading companies such as Carpigiani Group, IMA, Bonfiglioli Riduttori, SACMI, Poggipollini, MEP, Philip Morris International, EMAG, Siemens, PTC, VM Motori, Elenos, etc., that led to important scientific and commercial results and 3 international patents. These research activities date as back as 2007, when he led the design of the Teorema Big Data platform for Carpigiani Group, that is currently in use to remotely control almost 30,000 (thirty thousand) ice cream making machines operating all around the world, whose adoption allowed to reduce after-sales assistance costs supported by Carpigiani Group worldwide by 25%. He is the lead of the Big Data ab of the MechLav Technopole Laboratory: which participates in many research projects that involve the study and implementation of Big Data platforms for Industry 4.0 applications (https://ds.unife.it/industrial_research/).

He has co-authored over 90 articles in the distributed systems research area, with particular reference to IoT solutions in industrial and military environments, Cloud and Fog computing, wireless middleware, and IT service management. He serves as associate editor for IEEE Transactions on Network and Service Management, Hindawi/Wiley Wireless Communications and Mobile Computing Journal, and Wiley International Journal of Network Management, and routinely participates in the organization of the main international conferences and workshops in the network and service management and in the military communications research communities. He has active collaborations with several research institutions, such as IBM TJ Watson, Florida Institute for Human & Machine Cognition (IHMC), St. John’s University, and NATO Communications and Information Agency (NCIA).

Talk Title: Big Data for Industry 4.0: Use Cases from the Packaging Valley

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Talk Abstract

The development of modern communication systems allows to connect industrial equipment to the Internet, paving the way to the so called Industry 4.0 revolution. One of the world leading district for digital manufacturing is Emilia-Romagna (ER), the Italian region surrounding Bologna. Possibly best known in the world as the "Motoring Valley", because of the many renowned motoring brands located there, ER really is the "Packaging Valley" - where a plethora of automated packaging machines are produced. In their goal of producing smarter and smarter machines that bring an ever greater value to their customers, many of the manufacturing companies in the Packaging Valley have increasingly adopted both current and forward-looking ICT technologies to innovate their products and processes. This talk will provide an overview of relevant and important use cases, and discuss the most important lessons learned.

More specifically, we will present several compelling applications, fundamentally involving two main environments: "smart shop floor / smart factory" and "smart products", i.e. intelligent devices explicitly designed to operate outside the factory without supervision and to create B2B and B2B2C services. We will discuss high impact research activities whose main objective is overcoming the limits of traditional analytics solutions available on the market, analyzing how to build platforms Big Data of general applicability in Industry 4.0 for the analysis of data from different types of machines at different levels of abstraction (single machine, production line and multiline or multi-plant) and contextual storage of the collected data in order to optimize the use of resources.