While WP 2 is centered on the physical aspects of deploying a sensing campus, WP 3 is addressing all the problems of how to providing the information available from the sensing infrastructure (both real and virtual) to external elements, in an efficient, transparent and reliable way. Several problems need to be addressed to achieve this, from the development of mechanisms to support the interaction of multiple (and potentially different) sources of data, without mutual interference, and in a reliable way (Task 3.1); to the provision of a common environment for information access and distribution (Task 3.2); and to the development of generic enablers that can be used to simplify and enhance the massive amount of information available through this infrastructure (Task 3.2).
|2017-10-16||Networking System Definition and Development (M3-M32)||This task focuses on the definition and development of enhancements over M2M communication systems that allow an integrative horizontalization of different kinds of devices and access technologies, with the aim of creating a more uniform and flexible information interexchange between those elements and the services platforms that consume their information. Currently, smart environments communication systems that involve sensor devices are based on vertical solutions that, despite fitting (potentially in an optimal way) to the required function, do not consider (or consider in a very narrow way) the interaction with other systems, thus, limiting the creation of truly smart ecosystems. Such factors impact different aspects that stretch from the system evolution potential and interaction, to equipment selection and to the (greater or lesser) reduction of manufacturer dependence. In the past, different strategies have been taking form, towards multi-technology integration (not only in terms of different kinds of devices but also on different kinds of access network technologies), but with no clear victor. This way, the communications system design in this environment will focus on the data access control aspect, integrating it with support mechanisms based on cloud and virtualization aspects, as well as researching and applying data flow management mechanisms based in new developments of Software Defined Networking approaches. As such, the physical deployment developed inside Task 2.1 (and the existing assets inside the Campus, both at the networking and a sensing levels) and the optimization algorithms developed inside Task 2.2, will be taken in consideration, assuming always a potentially variable environment. Concretely, the task will consider dynamic gateway and sensor device elements (even with power constraints, as in Task 2.3) - potentially these elements can, on one hand, access the specific communication infrastructure of each system and, in the other, can couple network functions in a dynamic and on-demand way, whenever necessary. In this way, when a certain access to a specific sensor service demands an isolated feature from the network to allow access to its data, such feature can be dynamically instantiated in a cloud environment, with data flow management mechanisms (via SDN concepts, coupled with deployments inside Task 2.1) allowing its control. The system will thus allow the instantiation of the necessary network function, in order to interact with the specific sensor network data, channeling the information towards the requesting service. This process can benefit from enriching factors, such as optimized service (or sensor) connectivity to the network, or obtaining context information about that network connectivity point in order to optimize the service provisioning (i.e., in a video service it can become possible to reduce the video quality in real time, when the network conditions are not sufficient for the full quality). The task will also provide a more generalized and flexible way of interacting and querying the information from sensors, by researching and deploying new content-based procedures based on Information Centric Networking developments. In this scope, this task will be executed in parallel with Tasks 3.2 and 3.3., having as guidelines the scenarios identified in Task 1.1, the technologies identified in Task 1.2, and the realizations developed inside WP 2. This task is projected to have two interaction points with Task 6.1 (for integration and evaluation), aiming to allow a preliminary test with the other systems and, in its final variant, allow the delivery of the finalized system.|
|2017-10-16||Information Enhancement (M7-M26)||This task aims to provide the final solution with a set of high level services capable of work the large quantity of collected data (Big Data) and provide enhanced information from it. It also considers the development of reusable micro-services which can be deployed in service composition and orchestration scenarios. It is vital for this task that the storage and extraction services have to be generic and reusable in different scenarios. This approach aims to allow the integration of such services under the umbrella of services offered by the communication and data transmission network, in a processing and storage capability distribution logic throughout the whole network, following the Fog Computing Paradigm. This will imply a novel and distributed information storage system. This approach also intends to reuse capabilities installed at the Santiago Campus (but not necessarily centralized in Data Center) with the clear benefit of pre-existent infrastructure reutilization, such as existing computer laboratories which can operate as nodes for the distributed data storage system, or computational nodes for the knowledge extraction services. The storage and extraction services to be developed will allow the execution of the scenarios proposed by Task 1.1, as well as provide support to the integrating services from Task 3.3, and will be potentially explored for final application by WP 4 and WP 5. These services will be made available to the academic community through programmatic API’s, supported by open-source usage examples, and will be a key element for Task 6.2.|
|2017-10-16||Integrating Services (M3-M33)||This task considers the development of services that truly activate the different sensor devices elements and network mechanisms, in the deployment of a specific scenario. These services will be designed considering the proposed scenarios identified for a university campus, taking into consideration the specific requirements and benefits of an integrated multi-layer solution for the communication and processing of multi-source sensor data. Particularly, the exploitation of advanced control capabilities over the communication layers will be of extreme importance, making use of real-time and low-latency information processing mechanisms. The developed services, whenever relevant, will be integrated with the already existing computation platforms from the Santiago Campus, thus acting as tools which, despite having a disruptive operational nature, improve the Campus efficiency without partitioning it. Large scale event processing approaches will be followed, supported by Cloud processing platforms, as well as by the provisioning of standardized API’s following the best Open Data and transparency practices. Finally, it is expected that the developed and evaluated services allow the demonstration of a flexible services platform with a completely software-oriented management approach. This is the task that will provide the software infrastructure over which application-oriented activities will rely|