Platforms and Protocols for the Internet of Things

Building a general architecture for the Internet of Things (IoT) is a very complex task, exacerbated by the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we identify the main blocks of a generic IoT architecture, describing their features and requirements, and analyze the most common approaches proposed in the literature for each block. In particular, we compare three of the most important communication technologies for IoT purposes, i.e., REST, MQTT, and AMQP, and we also analyze three IoT platforms: openHAB, Sentilo, and Parse. The analysis will prove the importance of adopting an integrated approach that jointly addresses several issues and is able to flexibly accommodate the requirements of the various elements of the system. We also discuss a use case which illustrates the design challenges and the choices to make when selecting which protocols and technologies to use

Semantic Web Technologies Meet BIM for Accessing and Understanding Cultural Heritage

Within the EU funded project INCEPTION – Inclusive Cultural Heritage in Europe through 3D semantic modelling, the key-targeted achievement is the development of a specific cloud based platform, in order to accomplish the main objectives of accessing, understanding and strengthening European Cultural Heritage by means of enriched 3D models. The whole INCEPTION project is based on the close connection between state-of-the-art architectural modeling technologies (BIM, Building Information Modeling) and the latest cutting-edge web technologies. The platform is grounded on semantic web technologies and makes extensive use of WebGL and RESTful APIs, in order to enrich heritage 3D models by using Semantic Web standards. The INCEPTION platform will be a space for interchange of information and for the dialogue among professionals, students, scholars, curators, non-expert users, etc. Furthermore, the Semantic Web structure interlinks the platform with external Cultural Heritage available linked data and makes it gradually enhanced by specific flexible data structures provided as project specific ontologies. The paper will describe solutions based on the match between BIM, Cloud and Semantic Web

EXPRESS: Resource-oriented and RESTful Semantic Web services

This thesis investigates an approach that simplifies the development of Semantic Web services (SWS) by removing the need for additional semantic descriptions.The most actively researched approaches to Semantic Web services introduce explicit semantic descriptions of services that are in addition to the existing semantic descriptions of the service domains. This increases their complexity and design overhead. The need for semantically describing the services in such approaches stems from their foundations in service-oriented computing, i.e. the extension of already existing service descriptions. This thesis demonstrates that adopting a resource-oriented approach based on REST will, in contrast to service-oriented approaches, eliminate the need for explicit semantic service descriptions and service vocabularies. This reduces the development efforts while retaining the significant functional capabilities.The approach proposed in this thesis, called EXPRESS (Expressing RESTful Semantic Services), utilises the similarities between REST and the Semantic Web, such as resource realisation, self-describing representations, and uniform interfaces. The semantics of a service is elicited from a resource’s semantic description in the domain ontology and the semantics of the uniform interface, hence eliminating the need for additional semantic descriptions. Moreover, stub-generation is a by-product of the mapping between entities in the domain ontology and resources.EXPRESS was developed to test the feasibility of eliminating explicit service descriptions and service vocabularies or ontologies, to explore the restrictions placed on domain ontologies as a result, to investigate the impact on the semantic quality of the description, and explore the benefits and costs to developers. To achieve this, an online demonstrator that allows users to generate stubs has been developed. In addition, a matchmaking experiment was conducted to show that the descriptions of the services are comparable to OWL-S in terms of their ability to be discovered, while improving the efficiency of discovery. Finally, an expert review was undertaken which provided evidence of EXPRESS’s simplicity and practicality when developing SWS from scratch

Microservice-based Reference Architecture for Semantics-aware Measurement Systems

Cloud technologies have become more important than ever with the rising need for scalable and distributed software systems. A pattern that is used in many such systems is a microservice-based architecture (MSA). MSAs have become a blueprint for many large companies and big software systems. In many scientific fields like energy and environmental informatics, efficient and scalable software systems with a primary focus on measurement data are a core requirement. Nowadays, there are many ways to solve research questions using data-driven approaches. Most of them have a need for large amounts of measurement data and according metadata. However, many measurement systems still follow deprecated guidelines such as monolithic architectures, classic relational database principles and are missing semantic awareness and interpretation of data. These problems and the resulting requirements are tackled by the introduction of a reference architecture with a focus on measurement systems that utilizes the principles of microservices. The thesis first presents the systematic design of the reference architecture by using the principles of Domain-driven Design (DDD). This process ensures that the reference architecture is defined in a modular and sustainable way in contrast to complex monolithic software systems. An extensive scientific analysis leads to the core parts of the concept consisting of the data management and semantics for measurement systems. Different data services define a concept for managing measurement data, according meta data and master data describing the business objects of the application implemented by using the reference architecture. Further concepts allow the reference architecture to define a way for the system to understand and interpret the data using semantic information. Lastly, the introduction of a frontend framework for dashboard applications represents an example for visualizing the data managed by the microservices

Mobile Cloud Support for Semantic-Enriched Speech Recognition in Social Care

Nowadays, most users carry high computing power mobile devices where speech recognition is certainly one of the main technologies available in every modern smartphone, although battery draining and application performance (resource shortage) have a big impact on the experienced quality. Shifting applications and services to the cloud may help to improve mobile user satisfaction as demonstrated by several ongoing efforts in the mobile cloud area. However, the quality of speech recognition is still not sufficient in many complex cases to replace the common hand written text, especially when prompt reaction to short-term provisioning requests is required. To address the new scenario, this paper proposes a mobile cloud infrastructure to support the extraction of semantics information from speech recognition in the Social Care domain, where carers have to speak about their patients conditions in order to have reliable notes used afterward to plan the best support. We present not only an architecture proposal, but also a real prototype that we have deployed and thoroughly assessed with different queries, accents, and in presence of load peaks, in our experimental mobile cloud Platform as a Service (PaaS) testbed based on Cloud Foundry

Handling Live Sensor Data on the Semantic Web

The increased linking of objects in the Internet of Things and the ubiquitous flood of data and information require new technologies in data processing and data storage in particular in the Internet and the Semantic Web. Because of human limitations in data collection and analysis, more and more automatic methods are used. Above all, these sensors or similar data producers are very accurate, fast and versatile and can also provide continuous monitoring even places that are hard to reach by people. The traditional information processing, however, has focused on the processing of documents or document-related information, but they have different requirements compared to sensor data. The main focus is static information of a certain scope in contrast to large quantities of live data that is only meaningful when combined with other data and background information. The paper evaluates the current status quo in the processing of sensor and sensor-related data with the help of the promising approaches of the Semantic Web and Linked Data movement. This includes the use of the existing sensor standards such as the Sensor Web Enablement (SWE) as well as the utilization of various ontologies. Based on a proposed abstract approach for the development of a semantic application, covering the process from data collection to presentation, important points, such as modeling, deploying and evaluating semantic sensor data, are discussed. Besides the related work on current and future developments on known diffculties of RDF/OWL, such as the handling of time, space and physical units, a sample application demonstrates the key points. In addition, techniques for the spread of information, such as polling, notifying or streaming are handled to provide examples of data stream management systems (DSMS) for processing real-time data. Finally, the overview points out remaining weaknesses and therefore enables the improvement of existing solutions in order to easily develop semantic sensor applications in the future

Designing a Smart City Internet of Things Platform with Microservice Architecture

The Internet of Things (IoT) is being adopted in different application domains and is recognized as one of the key enablers of the Smart City vision. Despite the standard-ization efforts and wide adoption of Web standards and cloud computing technologies, however, building large-scale Smart City IoT platforms in practice remains challenging. The dynamically changing IoT environment requires these systems to be able to scale and evolve over time adopting new technologies and requirements. In response to the similar challenges in building large-scale distributed applications and platforms on the Web, microservice architecture style has emerged and gained a lot of popularity in the industry in recent years. In this work, we share our early experience of applying the microservice architecture style to design a Smart City IoT platform. Our experience suggests significant benefits provided by this architectural style compared to the more generic Service-Oriented Architecture (SOA) approaches, as well as highlights some of the challenges it introduces

CHAIN-REDS DART Challenge

CHAIN-REDS (Coordination and Harmonisation of Advanced e-infrastructure for Research and Education Data Sharing) is EU project focused on promoting and supporting technological and scientific collaboration across different communities established in various continents. Nowadays, one of the most challenging scenarios scientist and scientific communities are facing is huge amount of data emerging from vast networks of sensors and form computational simulations performed in a diversity of computing architectures and e-infrastructure. The new knowledge coming out from the interpretation of these datasets, reported on the scholar literature, is increasingly problematic to be reproducible due to the difficulty to access measured data repositories and/or computational applications that generate synthetic data through computer simulations. This paper presents CHAIN REDS approach, several tools and services, based on the adoption of standards, aimed at providing easy/seamless access to datasets, data repositories, open access document repositories and to the applications that could make use of them. All these tools and services are enclosed in what we have called the Data Accessibility, Reproducibility and Trustworthiness (DART) challenge. This initiative allows researchers to easily find data of his interest and directly use them in a code running by means of a Science Gateway (SG) that provides access to cluster, Grid and Cloud infrastructure worldwide. In this scenario, the datasets are found by means of either the CHAIN-REDS Knowledge Base (KB) or the Semantic Search Engine (SSE), the applications ran on the CHAIN-REDS SG, accessible through an Identity Federation. The datasets can be both identified by Persistent Identifier (PID) and assigned unique number ID. Scientists can then access the data and the corresponding application in order to either reproduce and extend the results of a given study or start a new investigation. The new data (and the new paper if any) are stored on the Data Infrastructure and can be easily found by the people belonging to the same domain making possible to start the cycle again.Repositório de dados científicos.Ibero-American Science and Technology Education Consortium (ISTEC

Application-agnostic Personal Storage for Linked Data

Personaalsete andmete ristkasutuse puudumine veebirakenduste vahel on viinud olukorrani, kus kasutajate identiteet ja andmed on hajutatud eri teenusepakkujate vahel. Sellest tulenevalt on suuremad teenusepakkujad, kel on rohkem teenuseid ja kasutajaid,\n\rväiksematega võrreldes eelisseisus kasutajate andmete pealt lisandväärtuse, sh analüütika, pakkumise seisukohast. Lisaks on sellisel andmete eraldamisel negatiivne mõju lõppkasutajatele, kellel on vaja sarnaseid andmeid korduvalt esitada või uuendada eri teenusepakkujate juures vaid selleks, et kasutada teenust maksimaalselt. Käesolevas töös kirjeldatakse personaalse andmeruumi disaini ja realisatsiooni, mis lihtsustab andmete jagamist rakenduste vahel. Lahenduses kasutatakse AppScale\n\rrakendusemootori identiteedi infrastruktuuri, millele lisatakse personaalse andmeruumi teenus, millele ligipääsu saab hallata kasutaja ise. Andmeruumi kasutatavus eri kasutuslugude jaoks tagatakse läbi linkandmete põhimõtete rakendamise.Recent advances in cloud-based applications and services have led to the continuous replacement of traditional desktop applications with corresponding SaaS solutions. These cloud applications are provided by different service providers, and typically manage identity and personal data, such as user’s contact details, of its users by its own means.\n\rAs a result, the identities and personal data of users have been spread over different applications and servers, each capturing a partial snapshot of user data at certain time moment. This, however, has made maintenance of personal data for service providers difficult and resource-consuming. Furthermore, such kind of data segregation has the overall negative effect on the user experience of end-users who need to repeatedly re-enter and maintain in parallel the same data to gain the maximum benefit out of their applications. Finally, from an integration point of view – sealing of user data has led to the adoption of point-to-point integration models between service providers, which limits the evolution of application ecosystems compared to the models with content aggregators and brokers.\n\rIn this thesis, we will develop an application-agnostic personal storage, which allows sharing user data among applications. This will be achieved by extending AppScale app store identity infrastructure with a personal data storage, which can be easily accessed by any application in the cloud and it will be under the control of a user. Usability of data is leveraged via adoption of linked data principles