A Development Framework Enabling the Design of Service-Based Cloud Applications

Cloud application platforms gain popularity and have the potential to change the way applications are developed, involving composition of platform basic services. In order to enhance the developer’s experience and reduce the barriers in the software development, a new paradigm of cloud application creation should be adopted. According to that developers are enabled to design their applications, leveraging multiple platform basic services, independently from the target application platforms. To this end, this paper proposes a development framework for the design of service-based cloud applications comprising two main components: the meta-model and the Platform Service Manager. The meta-model describes the building blocks which enable the construction of Platform Service Connectors in a uniform way while the Platform Service Manager coordinates the interaction of the application with the concrete service providers and further facilitates the administration of the deployed platform basic services

Orchestrating applications with TOSCA and Docker

The objective of this thesis was to contribute to automating the deployment of (complex) applications over heterogeneous infrastructures, by trying to combine the orthogonal approaches proposed by TOSCA and Docker. After analysing the state of the art, we designed and prototyped TosKer – the first engine (at the best of our knowledge) that is capable to input a TOSCA description of a multi-component application, and to automatically deploy and orchestrate it on top of Docker

System for Cross-domain Identity Management palveluiden pääsynhallintaan palvelupohjaisessa arkkitehtuurissa

Identity and Access Management systems are usually fundamental services in organizations. In Service-Oriented Architecture (SOA) they can be used to provide three different services: authentication, authorization and information about users and their access rights. For the latter, there has not been a widely used standard in SOA to provide user information to other services. System for Cross-domain Identity Management (SCIM) is a new emerging Representational state transfer (REST) based standard to help provision user information to cloud services. This Master Thesis discusses how SCIM can be used to provide user information to consuming services in a SOA based solution. The first part of the thesis studies what are the advantages and disadvantages using REST based solutions compared to SOAP based solutions. Based on a literary review, REST has better performance, measured by throughout put, and it is independent of data format. SOAP has the advantage of being very standardized and has mature tools and frameworks compared to REST. REST is more based on conventions than standards, so tools and frameworks behave differently which might lead to interoperability problems. The second part of the thesis focuses on whether SCIM can be used to provide user information service to consuming services. Three scenarios were designed and implemented in SCIM to find out whether the access right model of the SCIM is expressive enough and whether the resources defined by SCIM provide a required set of attributes. The presented scenarios have different requirements: the first one models internal access rights of an organization, the second scenario a use case in which an organization offers services to its customers and the third one a use case in which role based access rights are restricted to certain objects. The last two scenarios required extending the SCIM core resource schema. The models were tested in a proof-of-concept implementation and they were able to fulfill all the requirements. This indicates that SCIM can be used to implement user and user’s access right information service. To conclude, a five step process is presented that an organization can use to assess if SCIM is suitable for its use

A Model to support the decision process for migration to cloud computing.

Cloud computing is an emerging paradigm for provisioning computing and IT services. Migration from traditional systems setting up to cloud computing is a strategic organisational decision that can affect organisations’ performance, productivity, and growth as well as competitiveness. Organisations wishing to migrate their legacy systems to the cloud often need to go through a difficult and complicated decision-making process. This can be due to multiple factors including restructuring IT resources, the still evolving nature of the cloud environment, and the continuous expansion of the cloud services, configurations and providers. This research explores the factors that would influence decision making for migration to the cloud, its impact on IT management, and the main tasks that organisations should consider to ensure successful migration projects. The sequential exploratory strategy is followed for the exploration. This strategy is implemented through the utilisation of a two-stage survey for collecting the primary data. The analysis of the two-stage survey as well as the literature identified eleven determinants that increase the complexity in the decisions to migrate to the cloud. In the literature some of those determinants were realised, accordingly, there have been many proposed methods for supporting migration to the cloud. However, no systematic decision making process exists that clearly identifies the main steps and explicitly describes the tasks to be performed within each step. This research aims to fill this need by proposing a model to support the decision process for migrating to cloud. The model provides a structure which covers the whole process of migration decisions. It guides decision makers through a step-by-step approach aiding organisations with their decision making. The model was evaluated by exploring the views of a group of the cloud practitioners on it. The analysis of the views demonstrated a high level of acceptance by the practitioners with regard to the structure, tasks, and issues addressed by the model. The model offers an encouraging preliminary structure for developing a cloud Knowledge-Based Decision Support System

Une approche basée sur les lignes de produits logiciels pour la configuration et adaptation des environments multi-nuages

Cloud computing is characterized by a model in which computing resources are delivered as services in a pay-as-you-go manner, which eliminates the need for upfront investments, reducing the time to market and opportunity costs. Despite its benefits, cloud computing brought new concerns about provider dependence and data confidentiality, which further led to a growing trend on consuming resources from multiple clouds. However, building multi-cloud systems is still very challenging and time consuming due to the heterogeneity across cloud providers' offerings and the high-variability in the configuration of cloud providers. This variability is expressed by the large number of available services and the many different ways in which they can be combined and configured. In order to ensure correct setup of a multi-cloud environment, developers must be aware of service offerings and configuration options from multiple cloud providers.To tackle this problem, this thesis proposes a software product line-based approach for managing the variability in cloud environments in order to automate the setup and adaptation of multi-cloud environments. The contributions of this thesis enable to automatically generate a configuration or reconfiguration plan for a multi-cloud environment from a description of its requirements. The conducted experiments aim to assess the impact of the approach on the automated analysis of feature models and the feasibility of the approach to automate the setup and adaptation of multi-cloud environments.Le cloud computing est caractérisé par un modèle dans lequel les ressources informatiques sont fournies en tant qu'un service d'utilité, ce qui élimine le besoin de grands investissements initiaux. Malgré ses avantages, le cloud computing a suscité de nouvelles inquiétudes concernant la dépendance des fournisseurs et la confidentialité des données, ce qui a conduit à l'émergence des approches multi-cloud. Cependant, la construction de systèmes multi-cloud est toujours difficile en raison de l'hétérogénéité entre les offres des fournisseurs de cloud et de la grande variabilité dans la configuration des fournisseurs de cloud. Cette variabilité est caractérisé par le grand nombre de services disponibles et les nombreuses façons différentes de les combiner et de les configurer. Afin de garantir la configuration correcte d'un environnement multi-cloud, les développeurs doivent connaître les offres de services et les options de configuration de plusieurs fournisseurs de cloud.Pour traiter ce problème, cette thèse propose une approche basée sur les lignes de produits logiciels pour gérer la variabilité dans les cloud afin d'automatiser la configuration et l'adaptation des environnements multi-cloud. Les contributions de cette thèse permettent de générer automatiquement un plan de configuration ou de reconfiguration pour un environnement multi-cloud à partir d'une description de ses exigences. Les expérimentations menées visent à évaluer l'impact de l'approche sur l'analyse automatisée des modèles de caractéristiques et la faisabilité de l'approche pour automatiser la configuration et l'adaptation des environnements multi-nuages

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Semantic Systems. The Power of AI and Knowledge Graphs

This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies