Objective
On Earth Observation missions, payloads become more complex with more and more instruments collecting a huge amount of data that cannot be fully downloaded and needs to be processed on board. Most of the existing solutions allowing deployment and orchestration of applications at the edge relies on de-facto standard technologies coming from the cloud computing area but the community recognizes a need to adapt them for edge computing contexts such as space systems. Furthermore, ground-based data processing introduces latency between acquisition and production of the information to the end-user. Specific challenges also raise like the dynamic changes of the communication links in terms of network topology, or connectivity, like the energy saving concern, or like cybersecurity issues. To cope with this situation, Unikernel technology promises to be a game-changer as it allows to build lightweight and secure applications that can be deployed in any edge infrastucture. The ORCHIDE project aims to allow a safe and secure deployment and orchestration of image processing applications within Earth Observation satellites, whatever the HW processing resources, and whatever the hosting SW execution platform. The solution aims to be multi-mission / multi-users and to address a large range of services. Based on the end-user needs, a disruptive generic framework and Unikernel based solution will be developed to provide easier access to space with just a simple application that can be updated or even modified during all the satellite lifetime. It will be demonstrated that the ORCHIDE simulation solution can paves the way toward a Digital Twin of such Earth Observation Systems. The ORCHIDE’s impacts will be precious as it will enable scalable adaptable Missions for Meteo Environment Ocean & Observation/Reconnaissance mission and will integrate the green IT values as it enables the overall costs & power consumption optimization, thus allowing an overhead & energy footprint reduction.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesphysical sciencesastronomyobservational astronomyoptical astronomy
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networks
- natural sciencescomputer and information sciencescomputer security
- natural sciencescomputer and information sciencesdata sciencedata processing
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HORIZON-IA - HORIZON Innovation ActionsCoordinator
31100 Toulouse
France