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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - BRAIN-IoT (model-Based fRamework for dependable sensing and Actuation in INtelligent decentralized IoT systems)

Teaser

Summary

Modern applications in the IoT and CPS domain will be complex software ecosystems with strict requirements of geographic distribution, heterogeneity, dynamic evolution, security and privacy protection, highly more challenging than the ones required by the current environments. Two of the main challenges arising in the current Internet Of Things scenarios are, on oneside, the requirement of interconnecting several heterogeneous platforms and smart Things in the same environment and, on the other side, the need to be able to evolve the complex software ecosystem deployed, reacting automatically and at runtime to environmental changes, without the human intervention. To address these challenges, BRAIN-IoT establishes a framework and methodology supporting smart cooperative behaviour in fully decentralized, composable and dynamic federations of heterogeneous Internet of Things platforms. In this way, BRAIN-IoT enables smart autonomous behaviour in Internet of Things scenarios, involving heterogeneous sensors and actuators autonomously cooperating to execute complex, dynamic tasks. Furthermore, BRAIN-IoT enables dynamically deploying and orchestrating distributed applications, allowing the automatic installation and replacement of smart behaviours reacting to environmental changes and User events. Finally, BRAIN-IoT provides a set of components that guarantee the security and privacy protection of the data exchanged using the solution. BRAIN-IoT is a general purpose solution that aims at being adaptable for heterogeneous scenarios, from Service Robotics to Critical Infrastructure Management.

Work performed

During the first reporting period, the project focused on the work related to the project initiation, the requirements engineering and the specification definition processes, overall platform design, first prototypes development, demonstration definition and development.
Overall, BRAIN-IoT is driven by an iterative approach tailored to better bridge the gap between requirement analysis/elicitation and development activities.
The requirement engineering process has been initiated: vision scenarios and use cases were defined for the two considered application scenarios. The initial requirements were elicited, analysed and validated. First BRAIN-IoT IPR strategy and exploitation plan have been also defined.
Starting from the conceptual architecture, a reference architecture was designed. A BRAIN-IoT Federation is a geographically distributed entity composed of two or more BRAIN-IoT Fabrics; a BRAIN-IoT Fabric is a data-center centralized structure composed of one or more Fibres (each an OSGi framework); a Fibre may dynamically assemble composite OSGi functions or services, or where required, act as a local management agent controlling traditional applications deployed as container images. BRAIN-IoT Fabrics are self-contained entities with relocatable management services, which provide device discovery, search, composition and orchestration, allowing the rapid deployment of applications. Each BRAIN-IoT Fabric is able to dynamically deploy Smart Behaviours to appropriate resource within the environment in response to environmental triggers. The approach taken is conceptually similar to compute Lambdas made popular by Amazon Web Services (AWS); but more sophisticated in that the required behaviours are dynamically installed at the most appropriate points within a highly heterogeneous environment. The BRAIN-IoT federation achieves this by leveraging the Requirements and Capabilities metadata provided by default by all OSGi Bundles. To create Smart Behaviours, BRAIN-IoT framework includes model-based tooling that is compliant with Internet of Things Architecture (IoT-A) and optionally, via the use of Behavior, Interaction, and Priority (BIP) allows verifiability of runtime behaviours. The solution presented is part of the BRAIN-IoT framework that aims to support smart autonomous and cooperative behaviours across populations of heterogeneous Internet of Things (IoT) entities; an example of which may be heterogeneous agent-based CPS. For this population of entities, BRAIN-IoT also includes mechanisms to enforce privacy and data ownership; and uses open semantic models to enable inter-operable operations and exchange of data and control features between members. A primary requirement of BRAIN-IoT is to accommodate environmental and functional: i.e., environmentally triggered adaptations, where a new physical device/entity is encountered, which must be managed/interacted with; self-repair /re-optimization, where unforeseen failures occur within the environment or more appropriate resources are made available; adaptation to environment requests, spanning from simple cases, like scaling in response to load, to sophisticated behaviours. Smart Behaviours address these requirements. Each BRAIN-IoT Fabric is able to dynamically deploy them to appropriate resource within the environment in response to environmental triggers. If the required behaviours do not exist in either the runtime or the Smart Behaviour repository, then they may be rapidly created via the BRAIN-IoT modelling process. Sophisticated aggregate behaviours can be achieved via chaining together simpler behaviours: these behavioural chains are automatically assembled by each BRAIN-IoT Fabric.

Final results

The main ambitions to realize the innovation potential of the BRAIN-IoT Project are:
* Develop a technical framework suitable to foster reusability and convergence of IoT and CPS solutions: IoT and CPS have traditionally been two separate research and innovation fields. As CPS (and CPSoS) grow in scale, and IoT application needs start to involve actuation and dependable control, technical foundations for convergence needs to be built in order to facilitate re-use of existing solutions and exchange across the two fields. BRAIN-IoT will pave the way for such convergence to happen, opening new innovation fields and market opportunities.
* Foster the development of security- and privacy-aware systems in the IoT domain and beyond: as technology progresses, keeping privacy and security policy aligned becomes more and more difficult to achieve. BRAIN-IoT has the ambition to change this trend, by cross-linking application modelling and privacy policies modelling. Moreover, BRAIN-IoT will focus on all prevention aspects of security (confidentiality, integrity, and availability). To provide secure IoT solutions, BRAIN-IoT will propose methods and tools for the certification of safety, availability, secrecy, and trustworthiness across from the model to the platform.
* Develop innovative distributed management capabilities to support the creation and evolution of open IoT environments: while some existing platforms already support some federation capabilities, BRAIN-IoT aims at enhancing such federation capabilities to support a highly dynamic and heterogeneous environment and to develop innovative fully distributed management functionalities enabling the creation and deployment of IoT federated environments.
* Engage in a dissemination and standardization initiative that gives Europe a first-mover advantage: BRAIN-IoT has the ambition to standardize its high-profile achievements in open standardization groups in the IoT domain and beyond, resulting in more horizontal exploitation activities.