Sustainability of systems interoperability in dynamic business networks

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresCollaborative networked environments emerged with the spread of the internet, contributing to overcome past communication barriers, and identifying interoperability as an essential property to support businesses development. When achieved seamlessly, efficiency is increased in the entire product life cycle support. However, due to the different sources of knowledge, models and semantics, enterprise organisations are experiencing difficulties exchanging critical information, even when they operate in the same business environments. To solve this issue, most of them try to attain interoperability by establishing peer-to-peer mappings with different business partners, or use neutral data and product standards as the core for information sharing, in optimized networks. In current industrial practice, the model mappings that regulate enterprise communications are only defined once, and most of them are hardcoded in the information systems. This solution has been effective and sufficient for static environments, where enterprise and product models are valid for decades. However, more and more enterprise systems are becoming dynamic, adapting and looking forward to meet further requirements; a trend that is causing new interoperability disturbances and efficiency reduction on existing partnerships. Enterprise Interoperability (EI) is a well established area of applied research, studying these problems, and proposing novel approaches and solutions. This PhD work contributes to that research considering enterprises as complex and adaptive systems, swayed to factors that are making interoperability difficult to sustain over time. The analysis of complexity as a neighbouring scientific domain, in which features of interoperability can be identified and evaluated as a benchmark for developing a new foundation of EI, is here proposed. This approach envisages at drawing concepts from complexity science to analyse dynamic enterprise networks and proposes a framework for sustaining systems interoperability, enabling different organisations to evolve at their own pace, answering the upcoming requirements but minimizing the negative impact these changes can have on their business environment

NEGOSEIO: framework for the sustainability of model-oriented enterprise interoperability

Dissertation to obtain the degree of Doctor of Philosophy in Electrical and Computer Engineering(Industrial Information Systems)This dissertation tackles the problematic of Enterprise Interoperability in the current globally connected world. The evolution of the Information and Communication Technologies has endorsed the establishment of fast, secure and robust data exchanges, promoting the development of networked solutions. This allowed the specialisation of enterprises (particularly SMEs) and favoured the development of complex and heterogeneous provider systems. Enterprises are abandoning their self-centrism and working together on the development of more complete solutions. Entire business solutions are built integrating several enterprises (e.g., in supply chains, enterprise nesting) towards a common objective. Additionally, technologies, platforms, trends, standards and regulations keep evolving and demanding enterprises compliance. This evolution needs to be continuous, and is naturally followed by a constant update of each networked enterprise’s interfaces, assets, methods and processes. This unstable environment of perpetual change is causing major concerns in both SMEs and customers as the current interoperability grounds are frail, easily leading to periods of downtime, where business is not possible. The pressure to restore interoperability rapidly often leads to patching and to the adoption of immature solutions, contributing to deteriorate even more the interoperable environment. This dissertation proposes the adoption of NEGOSEIO, a framework that tackles interoperability issues by developing strong model-based knowledge assets and promoting continuous improvement and adaptation for increasing the sustainability of interoperability on enterprise systems. It presents the research motivations and the developed framework’s main blocks, which include model-based knowledge management, collaboration service-oriented architectures implemented over a cloud-based solution, and focusing particularly on its negotiation core mechanism to handle inconsistencies and solutions for the detected interoperability problems. It concludes by validating the research and the proposed framework, presenting its application in a real business case of aerospace mission design on the European Space Agency (ESA).FP7 ENSEMBLE, UNITE, MSEE and IMAGINE project

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

A UML Profile for the Design, Quality Assessment and Deployment of Data-intensive Applications

Big Data or Data-Intensive applications (DIAs) seek to mine, manipulate, extract or otherwise exploit the potential intelligence hidden behind Big Data. However, several practitioner surveys remark that DIAs potential is still untapped because of very difficult and costly design, quality assessment and continuous refinement. To address the above shortcoming, we propose the use of a UML domain-specific modeling language or profile specifically tailored to support the design, assessment and continuous deployment of DIAs. This article illustrates our DIA-specific profile and outlines its usage in the context of DIA performance engineering and deployment. For DIA performance engineering, we rely on the Apache Hadoop technology, while for DIA deployment, we leverage the TOSCA language. We conclude that the proposed profile offers a powerful language for data-intensive software and systems modeling, quality evaluation and automated deployment of DIAs on private or public clouds

Model driven validation approach for enterprise architecture and motivation extensions

As the endorsement of Enterprise Architecture (EA) modelling continues to grow in diversity and complexity, management of its schema, artefacts, semantics and relationships has become an important business concern. To maintain agility and flexibility within competitive markets, organizations have also been compelled to explore ways of adjusting proactively to innovations, changes and complex events also by use of EA concepts to model business processes and strategies. Thus the need to ensure appropriate validation of EA taxonomies has been considered severally as an essential requirement for these processes in order to exert business motivation; relate information systems to technological infrastructure. However, since many taxonomies deployed today use widespread and disparate modelling methodologies, the possibility to adopt a generic validation approach remains a challenge. The proliferation of EA methodologies and perspectives has also led to intricacies in the formalization and validation of EA constructs as models often times have variant schematic interpretations. Thus, disparate implementations and inconsistent simulation of alignment between business architectures and heterogeneous application systems is common within the EA domain (Jonkers et al., 2003). In this research, the Model Driven Validation Approach (MDVA) is introduced. MDVA allows modelling of EA with validation attributes, formalization of the validation concepts and transformation of model artefacts to ontologies. The transformation simplifies querying based on motivation and constraints. As the extended methodology is grounded on the semiotics of existing tools, validation is executed using ubiquitous query language. The major contributions of this work are the extension of a metamodel of Business Layer of an EAF with Validation Element and the development of EAF model to ontology transformation Approach. With this innovation, domain-driven design and object-oriented analysis concepts are applied to achieve EAF model’s validation using ontology querying methodology. Additionally, the MDVA facilitates the traceability of EA artefacts using ontology graph patterns

A Compositional Approach to Creating Architecture Frameworks with an Application to Distributed AI Systems

Artificial intelligence (AI) in its various forms finds more and more its way into complex distributed systems. For instance, it is used locally, as part of a sensor system, on the edge for low-latency high-performance inference, or in the cloud, e.g. for data mining. Modern complex systems, such as connected vehicles, are often part of an Internet of Things (IoT). To manage complexity, architectures are described with architecture frameworks, which are composed of a number of architectural views connected through correspondence rules. Despite some attempts, the definition of a mathematical foundation for architecture frameworks that are suitable for the development of distributed AI systems still requires investigation and study. In this paper, we propose to extend the state of the art on architecture framework by providing a mathematical model for system architectures, which is scalable and supports co-evolution of different aspects for example of an AI system. Based on Design Science Research, this study starts by identifying the challenges with architectural frameworks. Then, we derive from the identified challenges four rules and we formulate them by exploiting concepts from category theory. We show how compositional thinking can provide rules for the creation and management of architectural frameworks for complex systems, for example distributed systems with AI. The aim of the paper is not to provide viewpoints or architecture models specific to AI systems, but instead to provide guidelines based on a mathematical formulation on how a consistent framework can be built up with existing, or newly created, viewpoints. To put in practice and test the approach, the identified and formulated rules are applied to derive an architectural framework for the EU Horizon 2020 project ``Very efficient deep learning in the IoT" (VEDLIoT) in the form of a case study

Network Infrastructures for Highly Distributed Cloud-Computing

Software-Defined-Network (SDN) is emerging as a solid opportunity for the Network Service Providers (NSP) to reduce costs while at the same time providing better and/or new services. The possibility to flexibly manage and configure highly-available and scalable network services through data model abstractions and easy-to-consume APIs is attractive and the adoption of such technologies is gaining momentum. At the same time, NSPs are planning to innovate their infrastructures through a process of network softwarisation and programmability. The SDN paradigm aims at improving the design, configuration, maintenance and service provisioning agility of the network through a centralised software control. This can be easily achievable in local area networks, typical of data-centers, where the benefits of having programmable access to the entire network is not restricted by latency between the network devices and the SDN controller which is reasonably located in the same LAN of the data path nodes. In Wide Area Networks (WAN), instead, a centralised control plane limits the speed of responsiveness in reaction to time-constrained network events due to unavoidable latencies caused by physical distances. Moreover, an end-to-end control shall involve the participation of multiple, domain-specific, controllers: access devices, data-center fabrics and backbone networks have very different characteristics and their control-plane could hardly coexist in a single centralised entity, unless of very complex solutions which inevitably lead to software bugs, inconsistent states and performance issues. In recent years, the idea to exploit SDN for WAN infrastructures to connect multiple sites together has spread in both the scientific community and the industry. The former has produced interesting results in terms of framework proposals, complexity and performance analysis for network resource allocation schemes and open-source proof of concept prototypes targeting SDN architectures spanning multiple technological and administrative domains. On the other hand, much of the work still remains confined to the academy mainly because based on pure Openflow prototype implementation, networks emulated on a single general-purpose machine or on simulations proving algorithms effectiveness. The industry has made SDN a reality via closed-source systems, running on single administrative domain networks with little if no diversification of access and backbone devices. In this dissertation we present our contributions to the design and the implementation of SDN architectures for the control plane of WAN infrastructures. In particular, we studied and prototyped two SDN platforms to build a programmable, intent-based, control-plane suitable for the today highly distributed cloud infrastructures. Our main contributions are: (i) an holistic and architectural description of a distributed SDN control-plane for end-end QoS provisioning; we compare the legacy IntServ RSVP protocol with a novel approach for prioritising application-sensitive flows via centralised vantage points. It is based on a peer-to-peer architecture and could so be suitable for the inter-authoritative domains scenario. (ii) An open-source platform based on a two-layer hierarchy of network controllers designed to provision end-to-end connectivity in real networks composed by heterogeneous devices and links within a single authoritative domain. This platform has been integrated in CORD, an open-source project whose goal is to bring data-center economics and cloud agility to the NSP central office infrastructures, combining NFV (Network Function Virtualization), SDN and the elasticity of commodity clouds. Our platform enables the provisioning of connectivity services between multiple CORD sites, up to the customer premises. Thus our system and software contributions in SDN has been combined with a NFV infrastructure for network service automation and orchestration