OW2con'22

The H2020 MORPHEMIC Project Open Source Components
2022-06-09 , OW2con main virtual room

The talk will describe the MORPHEMIC open source components and the MORPHEMIC implementation integrated as a pre-processor for the existing MELODIC platform extending its deployment and adaptation capabilities beyond the multicloud and cross-cloud to the edge, 5G, and fog. The talk will then detail the open source strategy for the exploitation of the project results.


MORPHEMIC model adaptation is with the extension of the Open Source MELODIC project www.melodic.cloud in order to support live application reconfiguration. The former is when a component can run in different technical forms, i.e. in a Virtual Machine (VM), in a container, as a big data job, or as serverless components, etc. The technical form of deployment is chosen during the optimization process to fulfil the user’s requirements and needs. The quality of the deployment is measured by a user defined and application specific utility. Depending on the application’s requirements and its current workload, its components could be deployed in various forms in different environments to maximize the utility of the application deployment and the satisfaction of the user. Proactive adaptation is not only based on the current execution context and conditions but aims to forecast future resource needs and possible deployment configurations. This ensures that adaptation can be done effectively and seamlessly for the users of the application.

The MORPHEMIC deployment platform will therefore be very beneficial for heterogeneous deployment in distributed environments combining various Cloud levels including Cloud data centres, edge Clouds, 5G base stations, and fog devices. Advanced forecasting methods, including the ES-Hybrid method recently winning the M4 forecasting competition, will be used to achieve the most accurate predictions. The outcome of the project will be implemented in the form of the complete solution, starting from modelling, through profiling, optimization, runtime reconfiguration and monitoring. Then the MORPHEMIC implementation will be integrated as a pre-processor for the existing MELODIC platform extending its deployment and adaptation capabilities beyond the multicloud and cross-cloud to the edge, 5G, and fog. The talk wil then detail the open source strategy for the exploitation of the project results.

Dr. Alessandra Bagnato is a research scientist and the Recherche Responsible in Softeam Software (Docaposte Group). She holds a Ph.D. degree in Computer Science from TELECOM SudParis and Université Evry Val d’Essonne, France and a MSc in Computer Science from the University of Genoa, Italy. At Softeam, she leads the Softeam Software Modelio team research activities around innovative model-driven engineering methods in Modelio workbench in the area of Cyber-Physical Systems, Cloud and Big Data (like H2020 MORPHEMIC, ECSEL AIDO@Rt, H2020 Databio, H2020 CPSwarm, H2020 QRapids, H2020 CROSSMINER), GDPR and Privacy (H2020 PoSeID-on, ANR UPCARE) and on measuring software engineering (ITEA 3 MEASURE).

Paweł Skrzypek is a highly experienced architect of ICT systems, with extensive knowledge of machine learning and Big Data solutions. Chief Multi Cloud Architect, working on MELODIC project and other Cloud Computing projects, focusing on multi cloud and serverless approach.