Eco‐Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain Towards Digital Transition

The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects

Data distribution and exploitation in a global microservice artefact observatory

​© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cloud computing and specifically the microservice architecture pattern is becoming an increasingly prominent paradigm in computer science. Many modern cloud applications are composed of a variety of different microservices, each potentially built in different languages, using different technologies and a different software artefact structure. What is needed is the capability to monitor this rapidly expanding field and leverage the data to enable further research and development of microservice architectures. Drawing inspiration from the global observatories used in geoscience and astronomy, the aim of this research initiative is the establishment of a global observatory for microservice artefacts, allowing the aggregation of data from different hubs and the execution of dynamic analysis on them

Data Management in Microservices: State of the Practice, Challenges, and Research Directions

We are recently witnessing an increased adoption of microservice architectures by the industry for achieving scalability by functional decomposition, fault-tolerance by deployment of small and independent services, and polyglot persistence by the adoption of different database technologies specific to the needs of each service. Despite the accelerating industrial adoption and the extensive research on microservices, there is a lack of thorough investigation on the state of the practice and the major challenges faced by practitioners with regard to data management. To bridge this gap, this paper presents a detailed investigation of data management in microservices. Our exploratory study is based on the following methodology: we conducted a systematic literature review of articles reporting the adoption of microservices in industry, where more than 300 articles were filtered down to 11 representative studies; we analyzed a set of 9 popular open-source microservice-based applications, selected out of more than 20 open-source projects; furthermore, to strengthen our evidence, we conducted an online survey that we then used to cross-validate the findings of the previous steps with the perceptions and experiences of over 120 practitioners and researchers. Through this process, we were able to categorize the state of practice and reveal several principled challenges that cannot be solved by software engineering practices, but rather need system-level support to alleviate the burden of practitioners. Based on the observations we also identified a series of research directions to achieve this goal. Fundamentally, novel database systems and data management tools that support isolation for microservices, which include fault isolation, performance isolation, data ownership, and independent schema evolution across microservices must be built to address the needs of this growing architectural style

Conceptualizing a framework for cyber-physical systems of systems development and deployment

ABSTRACT Cyber-physical systems (CPS) refer to the next generation of embedded ICT systems that are interconnected, collaborative and that provide users and businesses with a wide range of smart applications and services. Software in CPS applications ranges from small systems to large systems, aka. Systems of Systems (SoS), such as smart grids and cities. CPSoS require managing massive amounts of data, being aware of their emerging behavior, and scaling out to progressively evolve and add new systems. Cloud computing supports processing and storing massive amounts of data, hosting and delivering services, and configuring selfprovisioned resources. Therefore, cloud computing is the natural candidate to solve CPSoS needs. However, the diversity of platforms and the low-level cloud programming models make difficult to find a common solution for the development and deployment of CPSoS. This paper presents the architectural foundations of a cloud-centric framework for automating the development and deployment of CPSoS service applications to converge towards a common open service platform for CPSoS applications. This framework relies on the well-known qualities of the microservices architecture style, the autonomic computing paradigm, and the model-driven software development approach. Its implementation and validation is on-going at two European and national projects

Creating a sustainable digital infrastructure: The role of service-oriented architecture

The United Nations’ goal of generating sustainable industry, innovation, and infrastructure is the point of departure for our reflective paper. The paper elaborates on the concepts of digital infrastructure, service-oriented architecture, and microservices. It emphasizes the benefits and challenges of creating a sustainable infrastructure based on a service-oriented environment, in which cloud services constitute an important part. We outline the prerequisites for obtaining a sustainable digital infrastructure based on services. Service-oriented architecture (SOA) and recently, microservice architecture, and cloud services, can provide organizations with the improved agility and flexibility essential for generating sustainability in a market focusing on digitalization. The reuse capability of SOA provides a common pool of information technology (IT) resources and qualifies as a green IT approach that impacts environmental protection. Previous research has identified IT and business alignment together with SOA governance as the most critical criteria when implementing SOA. This paper discusses these issues in-depth to explain sustainability.publishedVersio

Plataforma de serviços para monitorização da cadeia de valor do pescado

Traceability in the food value chain is a topic of interest due to the advantages it brings to both the consumers, producers and regulatory authorities. This thesis describes my contributions during the design and implementation of a microservice based middleware for the Portuguese fish value chain considering current practices in the industry and the requirements of the stakeholders involved in the project, with the goal of integrating all the traceability information available from each operator to provide customers with the full story of the products they purchase. During this project I assumed many roles such as development, operations and even some security allowing me to improve my skills in all these fields and experimenting with the latest cloud native technologies such as containers and with DevOps practices.A rastreabilidade na cadeia de valor alimentar é um tema de interesse pelas vantagens que traz aos consumidores, produtores e autoridades reguladoras. Esta dissertação descreve as minhas contribuições durante a conceção e implementação de um middleware baseado em micro-serviços para a cadeia de valor do pescado portuguesa considerando as práticas atuais da indústria e os requisitos das partes interessadas envolvidas no projeto, com o objetivo de integrar toda a informação de rastreabilidade disponível de cada um dos operadores para fornecer aos clientes a história completa dos produtos que adquirem. Durante este projeto, assumi muitas funções, como desenvolvimento, operações e até mesmo alguma segurança, o que me permitiu melhorar as minhas capacidades em todos essas disciplinas e experimentar as mais recentes tecnologias nativas da nuvem, como contentores e práticas de DevOps.Mestrado em Engenharia Informátic

Link layer Connectivity as a Service for Ad-hoc Microservice Platforms

Microservice platforms have brought many advantages to support the deployment of light-weight applications at both near the edge and data centers. Still, their suitability to support telecommunication and vertical services beyond the network edge is far from being a reality. On one hand, their flat networking approach does not support the establishment of link-layer connectivity among the different components of telecommunication and vertical services (e.g., access points, routers, specific-purpose servers, etc.) due to their reliance on high-level APIs. On the other hand, their networking approach has not been designed to operate over ad hoc networks built by the resource-constrained devices that may be available beyond the network edge. This can lead to suboptimal behaviors for the delivery of data traffic between microservices. This article presents the results of a research collaboration between Universidad Carlos III of Madrid and Telefónica: L2S-M. Our solution provides a programmable data plane that enables the establishment of on-demand link layer connectivity between microservices on ad hoc networks. This solution has the flexibility to execute different algorithms to build traffic paths between microservices, as well as to react against temporary link breakdowns, which could be present in these types of networks. The article presents a proof of concept for a functional validation of L2S-M, using an aerial ad hoc network deployed at 5TONIC Laboratory in collaboration with Telefonica. The validation results showcase the proper operation of L2S-M as a networking service for microservice platforms in ad hoc networks, including its ability to reconfigure the programmable data plane when link disruptions occur.This article has been supported by the TRUE5G (PID2019-108713RB681) project funded by the Spanish National Research Agency (MCIN/AEI/10.13039/5011000110) and by the H2020 FISHY Project (Grant agreement ID: 952644)

AIMS: An Automatic Semantic Machine Learning Microservice Framework to Support Biomedical and Bioengineering Research

The fusion of machine learning and biomedical research offers novel ways to understand, diagnose, and treat various health conditions. However, the complexities of biomedical data, coupled with the intricate process of developing and deploying machine learning solutions, often pose significant challenges to researchers in these fields. Our pivotal achievement in this research is the introduction of the Automatic Semantic Machine Learning Microservice Framework (AIMS). AIMS addresses these challenges by automating various stages of the machine learning pipeline, with a particular emphasis on the ontology of machine learning services tailored for the biomedical domain. This ontology encompasses everything from task representation, service modeling, and knowledge acquisition to knowledge reasoning and the establishment of a self-supervised learning policy. Our framework has been crafted to prioritize model interpretability, integrate domain knowledge effortlessly, and handle biomedical data with efficiency. Additionally, AIMS boasts a distinctive feature: it leverages self-supervised knowledge learning through reinforcement learning techniques, paired with an ontology-based policy recording schema. This enables it to autonomously generate, fine-tune, and continually adapt to machine learning models, especially when faced with new tasks and data. Our work has two standout contributions of demonstrating that machine learning processes in the biomedical domain can be automated, while integrating a rich domain knowledge base and providing a way for machines to have a self-learning ability, ensuring they handle new tasks effectively. To showcase AIMS in action, we've highlighted its prowess in three case studies from biomedical tasks. These examples emphasize how our framework can simplify research routines, uplift the caliber of scientific exploration, and set the stage for notable advances