Keynote
AI and Edge Computing: Driving Competitive Advantage for Businesses
In this era of rapid technological evolution, businesses are constantly seeking innovative ways to gain
a competitive edge and stay ahead of the curve. Edge Computing and Artificial Intelligence have emerged as
two pivotal technologies that can revolutionize how industries operate in an increasingly challenging global market.
The combination of these two new paradigms is expected to help organizations unlock new opportunities, enhance
operational efficiency, and ultimately drive business success. Based on IKERLAN’s first-hand experience as members of the Mondragon Corporation—the largest industrial
group in the Basque Country (Spain)—this Keynote will focus on examining the practical implementation of
edge-cloud solutions in EU strategic sectors such as Industry, Manufacturing, Transport, and Energy. This talk
will include real-world examples that demonstrate how open source solutions can contribute significantly to fostering
innovation within Europe and to maintaining the competitiveness of European businesses. This presentation will also describe a concrete example of successful R&D collaboration revolving around open source
edge cloud technologies: the COGNIT Project. Funded by the Horizon Europe program, this project will establish a novel
distributed Function-as-a-Service model for managing edge applications. This new AI-enabled platform is poised to
revolutionize the processing of data by allowing edge and IoT devices to easily offload heavy processing tasks to
the emerging multi-provider Cognitive Cloud Continuum. | Marco Conzalez Hierro | | | Session slides for session AI and Edge Computing: Driving Competitive Advantage for Businesses |
Session
Modular Monoliths the way to Standardization
In resent years monolith architecture gains once again a lot
of popularity, in order to reduce costs and time compared
to more complicated architectures. Taking into account the
advantages of micro-service, and trying to embed some of
them to monolith architectures, we come to the creation of
modular monoliths. This type of design can be consider quite
new, and so there isn’t yet a specific architecture design that
someone could follow if they wish to use it. In this paper
we present an architectural design and an implementation
strategy for modular monoliths. To evaluate the usefulness
of this architecture, we have conducted a study, validating
the design and its implementation. In this study 12 architects
from different companies took part, expressing some
concerns regarding the feasibility in bigger project but also
giving an overall positive feedback for the design. | Michael Tsechelidis | | Session slides for session Modular Monoliths the way to Standardization | Session slides for session Modular Monoliths the way to Standardization |
Session
Tool Support for Architectural Pattern Selection and Application in Cloud-centric Service-oriented IDEs
Architectural patterns are high level design guidelines and principles for software systems. They play a crucial role
laying the foundations to the organization and structure of software systems and have high impact on their quality and success
both in terms of business and engineering aspects. Deciding for a specific software architecture requires careful analysis of
several factors regarding the software system including system characteristics, constraints and required quality attributes,
and is often not trivial. This paper presents a framework for architectural pattern selection and application that supports
the decision-making process of choosing an appropriate architectural pattern, and the organization of the software structure
based on the chosen pattern in an automated fashion when integrated in IDEs. In particular, the paper presents how this framework
is implemented and integrated within an innovative open source cloud-native integrated development environment. | Feryal Fulya Horozal | | Session slides for session Tool Support for Architectural Pattern Selection and Application in Cloud-centric Service-oriented IDEs | Session slides for session Tool Support for Architectural Pattern Selection and Application in Cloud-centric Service-oriented IDEs |
Session
PIACERE Integrated Development Environment
This article presents a model-driven engineering (MDE) integrated
development environment (IDE) to assist the DevSecOps
(Development Security and Operations) process. This tool has been
developed within the PIACERE H2020 project, which proposes a
framework composed of a set of tools developed to support all
phases of the DevSecOps life cycle including modeling,
test/validation, build/generate, deployment, operate and modeling. PIACERE IDE is an Eclipse based tool, that acts as the front-end
for this framework, and plays a key role in integrating other
PIACERE tools. The IDE allows developers to access the different
tools in a simple and unified way. | Gorka Benguria Elguezabal | | Session slides for session PIACERE Integrated Development Environment | Session slides for session PIACERE Integrated Development Environment |
Session
LinkEdge: Open-sourced MLOps Integration with IoT Edge
MLOps, or Machine Learning Operations, play a significant role
in streamlining production deployment, monitoring, and management
of machine learning models. Integrating MLOps with edge
devices poses unique challenges that require customised deployment
strategies and efficient model optimisation techniques. This
paper introduces LinkEdge, a set of tools that enable the integration
of MLOps practices with edge devices. LinkEdge consists of two
sets of tools: one for setting up infrastructure within edge devices
to be able to receive, monitor, and run inference on ML models and
another for MLOps pipelines to package models to be compatible
with the inference and monitoring components of the respective
edge devices. The LinkEdge platform is evaluated by obtaining a
public dataset for predicting the breakdown of Air Pressure Systems
in trucks. Additionally, the platform is compared against a set of
commercial and open-source tools and services that serve similar
purposes. The overall performance of LinkEdge matches that of
already existing tools and services while allowing end users setting
up Edge-MLOps infrastructure the complete freedom to set up their
system without entirely relying on third-party licensed software. | Savidu Dias | Session video for session LinkEdge: Open-sourced MLOps Integration with IoT Edge | Session slides for session LinkEdge: Open-sourced MLOps Integration with IoT Edge | Session slides for session LinkEdge: Open-sourced MLOps Integration with IoT Edge |
Session
Enabling Compute and Data Sovereignty with Infrastructure-Level Data Spaces
Data is a critical asset in today’s world, and its value cannot be
overstated. However, ensuring that data is accessible only to authorized
parties and protecting it against theft present significant
challenges. A potential solution to these issues is creating data
spaces that interconnect clusters managed by different actors. The
latter can securely exchange data under specific constraints and
terminate connections when needed. This paper aims to show how
to create infrastructure-level data spaces to facilitate secure data
exchange and prevent data theft. Furthermore, we investigate how
data sovereignty can be maintained through cluster data exchange,
which is crucial in an era where data is increasingly regulated
and controlled. Additionally, we explore how offloading applications
from the data consumer into the data producer cluster can
match data gravity patterns, improving overall system efficiency. Finally,
this paper presents the potential integration of the proposed
solution within the framework of IDSA and Gaia-X, serving as
promising option for implementing their proposed functionalities. | Jacopo Marino | Session video for session Enabling Compute and Data Sovereignty with Infrastructure-Level Data Spaces | Session slides for session Enabling Compute and Data Sovereignty with Infrastructure-Level Data Spaces | Session slides for session Enabling Compute and Data Sovereignty with Infrastructure-Level Data Spaces |
Session
Feature Estimation for Punching Tool Wear at the Edge
As a fast and inexpensive machining method applicable for creating a wide range of shapes and
producing large batches, sheet metal punching is widely used e.g., in automotive, aerospace, electronics,
and construction industries. A significant downside of sheet metal punching is the punching tool wear
in use. A worn punch tool may impact the quality of the end product by causing imperfections and reduce
the efficiency of the manufacturing process through increased scrap and by slowing down the production. Effective monitoring of punching tool wear is therefore essential for an efficient and cost-effective
production of high-quality parts. The monitoring can be based on acceleration measurement which produces
large amounts of raw data, making edge processing ideal as only the indication of the tool condition needs
to be sent forward for decision support. Classification models for tool wear identification were built and
compared in this study. The models are based on measured acceleration data. Two different open-source methods
for time series feature extraction, namely TSFEL and MiniRocket, were tested and the classification results
based on them compared. All methods used for building the models are computationally light and therefore
applicable for real-time data processing at the edge. According to the results the MiniRocket algorithm is
suitable for the task and superior compared to the TSFEL method. The classification accuracies based on the
MiniRocket features are at best over 96.5 % and at worst around 84 %, whereas the corresponding accuracies
are between 35 and 56 % for TSFEL feature based models. The use of the MiniRocket algorithm in building a model
for punch tool monitoring shows very promising results. However, the dataset used was very limited.
Therefore, further investigation is required based on an ampler dataset. | Olli Saarela | Session video for session Feature Estimation for Punching Tool Wear at the Edge | Session slides for session Feature Estimation for Punching Tool Wear at the Edge | Session slides for session Feature Estimation for Punching Tool Wear at the Edge |
The European Computing Continuum: Initiatives, Community, and Directions
The convergence megatrend of Cloud Computing and IoT towards a computing continuum has been clearly recognised
at European level and is having significant innovation, economic, and policy impact. This transition is creating
a tremendous opportunity for Europe to demonstrate its ability to facilitate the implementation of sustainable,
resource-efficient, fair, and inclusive digital infrastructure. These first three years of the Horizon Europe
programme have seen several research and innovation initiatives start and gather momentum, while the originally
separated R&I communities around Cloud and IoT have increasingly come together in a new, seamless ecosystem:
EUCloudEdgeIoT provides coordination and support across this thriving landscape of projects and communities,
covering key horizontal enablers such as Open Source and Open Standards as well as verticalised stakeholder
engagement and market sectors. Further development is expected for 2024 and 2025, with new complementary
initiatives rolled out and updated vision and roadmap for Computing Continuum research. | Giovanni Rimassa | Session video for session The European Computing Continuum: Initiatives, Community, and Directions | | Session slides for session The European Computing Continuum: Initiatives, Community, and Directions |