Periodic Reporting for period 1 - SMARTEDGE (Semantic Low-code Programming Tools for Edge Intelligence)
Période du rapport: 2023-01-01 au 2023-12-31
SMARTEDGE project started on Jan 2023. Its prime objective is to enable the dynamic integration of de-centralised edge intelligence at runtime while ensuring reliability, security, privacy and scalability. SMARTEDGE will achieve this by enabling a semantic-based interplay of the edge devices of such systems via a cross-layer toolchain that facilitates the seamless and real-time discoverability and composability of autonomous intelligence swarm. Hence, an application can be freely built by distributing the processing, data fusion and control across heterogeneous sensors, devices and edges with ubiquitous low-latency connectivity.
The goal of this project is to develop a SMARTEDGE solution with a low-code tool programming environment with various tools as for example Continuous Semantic Integration; Dynamic Swarm Network; and Low-code Toolchain for Edge Intelligence. Continuous Semantic Integration allows the SMARTEDGE solution to interact with devices according to a standardized semantic interface, via a continuous conversion process based on declarative mappings and scalable from edge to cloud, and providing a declarative approach for the creation and orchestration of apps based on swarm intelligence. On the other hand, Dynamic Swarm Network provides the necessary automatic discovery and dynamic network swarm formation in near real time, hardware-accelerated in-network operations for context-aware swarm networking, as well as embedded network security. The low-code tool chain provides semantic-driven multi-modal stream fusion for Edge devices; swarm elasticity via Edge-Cloud Interplay, adaptive coordination and optimization and cross-layer toolchain for Device-Edge-Cloud Continuum. The SMARTEDGE solution will be comprehensively demonstrated over four application areas: automotive, city, factory and heath via the strong collaboration of the participating industrial partners.
The goal of this project is to develop a SMARTEDGE solution with a low-code tool programming environment with various tools as for example Continuous Semantic Integration; Dynamic Swarm Network; and Low-code Toolchain for Edge Intelligence. Continuous Semantic Integration allows the SMARTEDGE solution to interact with devices according to a standardized semantic interface, via a continuous conversion process based on declarative mappings and scalable from edge to cloud, and providing a declarative approach for the creation and orchestration of apps based on swarm intelligence. On the other hand, Dynamic Swarm Network provides the necessary automatic discovery and dynamic network swarm formation in near real time, hardware-accelerated in-network operations for context-aware swarm networking, as well as embedded network security. The low-code tool chain provides semantic-driven multi-modal stream fusion for Edge devices; swarm elasticity via Edge-Cloud Interplay, adaptive coordination and optimization and cross-layer toolchain for Device-Edge-Cloud Continuum. The SMARTEDGE solution will be comprehensively demonstrated over four application areas: automotive, city, factory and heath via the strong collaboration of the participating industrial partners.
During the first year of the project, requirements describing the functional scope of the desired SmartEdge toolset were defined based on the use cases and the project's internal expert knowledge. The requirements were collected in six different categories around Swarm Management, Swarm Communication, IDM and Policy & Security, Application Lifecycle, Hardware and Protocols, Continuous Semantic Integration and Low Code Programming. Based on each use case, use case partners were asked to identify their requirements for SmartEdge (making sure to differ between pure use case requirements and requirements to be met by SmartEdge). Stakeholders were also defined, i.e. the people who may interact with, use, or contribute to SmartEdge.
In addition, Use Cases scenarios were defined and execution plans were carried out. For each use case, detailed technical overviews, encompassing potential demonstration scenarios, outlining feasible functionalities, and specifying necessary supporting details of technical overviews were carried out.
Finally, the initial architecture for the SmartEdge project was outlined. Various implementation options were analysed considering Use Case scenarios and Smartedge toolset requirements.
The final architectural design considered many fundamental concepts of the SmartEdge design, such as “what is a swarm”, “can swarms have heterogeneous members”, and “is it possible to be part of two swarms at the same time”. These concepts were applied to the use cases to see if they met their functional requirements.
On going work in the second year focuses on developing all the necessary tools for Continuous Semantic Integration (CSI) concept as well as implementing the Dynamic Swarm Networking concept. This includes hardware-accelerated in-network operations for context-aware networking and automatic resource discovery.
In addition, Use Cases scenarios were defined and execution plans were carried out. For each use case, detailed technical overviews, encompassing potential demonstration scenarios, outlining feasible functionalities, and specifying necessary supporting details of technical overviews were carried out.
Finally, the initial architecture for the SmartEdge project was outlined. Various implementation options were analysed considering Use Case scenarios and Smartedge toolset requirements.
The final architectural design considered many fundamental concepts of the SmartEdge design, such as “what is a swarm”, “can swarms have heterogeneous members”, and “is it possible to be part of two swarms at the same time”. These concepts were applied to the use cases to see if they met their functional requirements.
On going work in the second year focuses on developing all the necessary tools for Continuous Semantic Integration (CSI) concept as well as implementing the Dynamic Swarm Networking concept. This includes hardware-accelerated in-network operations for context-aware networking and automatic resource discovery.
During the 1st of year of the project, the SmartEdge architectural solution has been defined. One of its prime objective that is under development concerns (Obj.2) “Middleware and tools for continuous semantic integration”. In particular, this concerns the concept and implementation of Continuous Semantic Integration. This concept is broken down into (i) Standardized Semantic Interfaces; (ii) DataOps toolbox for semantic management of things and embedded AI apps; (ii) Creation and orchestration of Swarm Intelligence apps. In the first months of the project, work in this task focused on the design of a set of standard interfaces and tools for common data access and continuous semantic integration. To this goal, results beyond the state of the art concerns the outline of SmartEdge Schema, the recipe Model used, domain Specific Ontologies and the standardization of the Semantic Interfaces.
Another important result of 1st year concerns network-layer aspects and particularly Obj.3: Dynamic Swarm Networking. Dynamic Swarm Networking entitles automatic discovery and dynamic network swarm formation in near real time, enhance hardware-accelerated in-network operations for context-aware swarm networking, and support embedded network security. During the first reporting period of the project, results concerned setting up development environments and identifying use case-to-tasks mapping and developing initial concepts for swarm formation, network security and in-network hardware acceleration.
Another important result of 1st year concerns network-layer aspects and particularly Obj.3: Dynamic Swarm Networking. Dynamic Swarm Networking entitles automatic discovery and dynamic network swarm formation in near real time, enhance hardware-accelerated in-network operations for context-aware swarm networking, and support embedded network security. During the first reporting period of the project, results concerned setting up development environments and identifying use case-to-tasks mapping and developing initial concepts for swarm formation, network security and in-network hardware acceleration.