A propos du centre ou de la direction fonctionnelle

The Centre Inria de l'Université de Grenoble groups together almost 600 people in 22 research teams and 7 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, ...), but also with key economic players in the area.

The Centre Inria de l'Université Grenoble Alpe is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Contexte et atouts du poste

The work will investigate model-based control of self-adaptive (re-)deployment of distributed applications on the Cloud-Edge infrastructures.

It will contribute to the Tasting project of the PEPR TASE, and more particularly to the objective of "better resilience and flexibility with enhanced digitalization" by making the ICT infrastructures supporting digitalization more flexible, and hence more efficient as well as more resilient.

It will involve cooperation amongst others with our industrial partner RTE.

Mission confiée

We consider the context where control and protection functions for energy transportation systems have to be executed on a distributed heterogeneous Cloud-Edge computing infrastructure, according to the needs and specificities of these applications.

In this context, this deployment also has to be reconfigured in a self-adaptive way, in a feedback loop according to variations and events at the different levels of application (e.g., variations in the need for precision in the control functions), infrastructure (e.g., loss or degradation of computing nodes, or of communication links) environment (e.g., heat wave compromising use of fan-less or airco-less nodes in edge posts, wind, rain or flooding).

We pursue software architectures that support separation of concerns between self-adaptations at the levels of computing and communication infrastructure (hardware), management and allocation of computing tasks implementing control and protection (middleware), and modes of the applications (business or process).

We will consider different reconfiguration strategies, according to criteria such as security properties, non-functional properties (e.g., latency), minimization of computing resources. The work will be specifically targeted at the application to an energy infrastructure, e.g., the use case from project partner RTE.

Principales activités

A first line of work consists of designing a model of configurations and reconfiguration strategies to support a decision method for choosing the next configuration most appropriate w.r.t. evolutions and events compliant with the reconfiguration strategy. The work can take inspiration and reuse results from earlier cooperative projects between Inria and RTE [Moghaddam2022, Chehida2024]. On the one hand, modelling will be investigated in terms of using constraints specification and solving e.g., Integer Linear Programming (ILP) methods and tools, to define variables characterizing configurations, and constraints between them and optimization objectives formalizing reconfiguration strategies. Options in different strategies will be analyzed to explore the potential design space, and give tools for application domain specialists to make choices. On the other hand, approaches to simulation tools (e.g., BatSim) will be studied, in order to support evaluation of these strategies confronted with realistic and at the same time appropriately abstracted models of target systems and use cases. A topic of interest is to study more generally the particularities of simulation of self-adaptive systems (i.e., simulating the effect of reconfiguration actions, in order to feed them into the feedback loop). An interesting perspective is to consider, not only the choice of the next configuration, but also constraints involved in complex reconfiguration processes, taking into account the assemblies of software components involved, their interactions and dependencies, implementation constraints, and temporal aspects.

Another line of work considers that the same approaches to management of self-adaptation in datacenters can be considered more generally, also concerning "client" datacenters, users of power transportation and supply: the curently observed fast rise in installation of new datacenters, and their concentration in specific geographical regions, is exposing energy transportation systems to challenging loads. The flexible management of these "client" datacenters can participate to a better coupling between energy network capacity variations and regulation of computing activity in datacenters, what RTE calls "systems services" or more generally flexibilities. For example, it is current practice the power supply to datacenters can be limited, with advance notification of a day or two, giving time to the former to self-adapt and downscale their activity in a form of graceful degradation. As can be seen, the same general approaches and mechanisms for model-based self-adaptive (re-)deployment of distributed applications can be considered, targeted at these "client" datacenters, with the objective that their flexibility can contribute to improve the management of power transportation and make it more flexible itself e.g., by lowering the advance notice delay. A related topic can be to consider how such an advance notice duration influences datacenter reconfiguration possibilities, and costs in terms of service degradation.

Compétences

Technical skills and knowledge appreciated are amongst:

• distributed systems
• modelling e.g., using contraints programming
• simulation

Avantages

• Subsidized meals
• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Social security coverage