A Glimpse in the H2020 PHYSICS Validation Scenarios and Use Cases

The main goal of PHYSICS is to unlock the potential of the Function-as-a-Service (FaaS) paradigm for Cloud Service Providers (CSP) and for Application Developers. Specifically, it will enable application developers to design, implement and deploy advanced FaaS applications in the scope of advanced cloud application design environments, leveraging proven design patterns and existing libraries of cloud/FaaS components. Furthermore, PHYSICS will offer a novel Global Continuum Layer that will undertake to deploy functions in optimal ways that will optimize multiple application objectives at the same time, including for example performance, latency, and cost.

PHYSICS will validate the benefits of its Global Continuum Layer and tools, in the scope of user-driven application scenarios in three important sectors, namely healthcare, agriculture and industry. Specifically:

  • PHYSICS in Manufacturing: The PHYSICS industrial use cases will focus on manufacturing and production. It will be deployed in a smart plant testbed to demonstrate how FaaS can be used to optimize production pipelines in environments where multiple edge devices (e.g., Cyber-Physical Systems (CPS)) are used. Specifically, FaaS enabled production pipelines based on heterogeneous devices that are currently available in the plant will be developed. The devices of the pilot plant include edge devices (e.g., Fujitsu INTELLIEDGE A700, HUAWEI ATLAS Edge Server), several HPC (High Performance Computing) Clusters or single HPCs, special GPU (Graphical Processing Units) enabled processing nodes (e.g., Nvidia DGXs), industrial PCs, PLCs (Programmable Logic Controllers), Single board computers, Raspberry Pis, as well as devices that simulate Quantum-like processes (i.e., Fujitsu Digital Annealing Unit). PHYSICS will facilitate the combination and use of services from these diverse setups in a seamless and integrated manner. Moreover, it will ensure that relevant FaaS functions for accessing the capabilities of these devices are assigned and used in optimally. The PHYSICS industrial/manufacturing use case is led by the German Research Centre for Artificial Intelligence.
  • PHYSICS in Healthcare: The PHYSICS healthcare use case will focus on the deployment of functions (FaaS) across multiple IoT edge devices (e.g., fitbit, wearables) and smart phones that provide Real-World Data and enable the extraction of novel biomarkers about certain diseases. PHYSICS FaaS functions will be optimized to address diverse needs about data access interfaces, data harmonization, and transformation, as well as different privacy and data protection requirements. Specifically, PHYSICS will boost the definition and execution of customized application logic for each different type of device, towards fulfilling data transmission requirements and data privacy constraints, and enabling the extraction of credible biomarkers. Likewise, PHYSICS will improve the scalability and extensibility of the biomarker extraction platform, through easing the deployment of new devices and data sources, subject to technical constraints and data protection requirements. The PHYSICS Healthcare use case is led by InnovationSprint Sprl.
  • PHYSICS in Agriculture: The PHYSICS Agriculture Use Case will showcase how the FaaS paradigm can facilitate the implementation of many thousands (i.e., from 500.000 to 1.000.000) of daily climatic simulations towards improving crop management and yield estimation. The scalable execution of thousands of simulations about each greenhouse is a key to manage meteorological uncertainty and correcting its trajectory with existing historical data. Specifically, FaaS will facilitate the optimal distribution and deployment of functions across different cloud environments and the local sites, in ways that ease (re)configuration of simulations towards an optimal distribution of computations across edge nodes and the cloud. Likewise, the use case will showcase a tangible performance improvement in the execution of simulation, including the possibility to execute simulations in near real-time. The PHYSICS Agriculture use case is led by CYBELETECH.


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