Description du projet
Les bases des réseaux d’auto-ajustement
Les réseaux sont des infrastructures essentielles et coûteuses, indispensables à notre société numérique. Les nouvelles technologies optiques reconfigurables ouvrent la voie à des réseaux auto-ajustables: des réseaux qui peuvent adapter dynamiquement leur topologie à la charge de travail qu’ils assument à un moment donné, améliorant ainsi leurs performances et leur efficacité globales. Le projet AdjustNet, financé par l’UE, jettera les bases des réseaux auto-ajustables en concevant des modèles, des mesures et des algorithmes pour l’adaptation de la topologie en ligne, puis procédera à leur validation grâce à des études de cas (par exemple: les réseaux de centres de données). Cette nouvelle méthodologie s’appuie sur les fascinantes intrications entre les réseaux auto-ajustables et les structures de données ainsi que sur la théorie de l’information.
Objectif
Communication networks have become a critical infrastructure of our digital society. However, with the explosive growth of data-centric applications and the resulting increasing workloads headed for the world’s datacenter networks, today’s static and demand-oblivious network architectures are reaching their capacity limits.
The AdjustNet project proposes a radically different perspective, envisioning demand-aware networks which can dynamically adapt their topology to the workload they currently serve. Such self-adjusting networks hence allow to exploit structure in the demand, and thereby reach higher levels of efficiency and performance. The vision of AdjustNet is timely and enabled by recent innovations in optical technologies which allow to flexibly reconfigure the physical network topology.
The goal of AdjustNet is to lay the theoretical foundations for self-adjusting networks. We will identify metrics that serve as yardstick of what can and cannot be achieved in a self-adjusting network for a given demand, devise algorithms for online adaption, and validate our framework through case studies. Our novel methodology is motivated by an intriguing connection of self-adjusting networks to known datastructures and to information theory.
AdjustNet comes with significant challenges since, similar to self-driving cars, self-adjusting networks require human network operators to give away control, and since more autonomous network operations may lead to instabilities. AdjustNet will overcome these risks and achieve its objectives by pursuing a rigorous approach, devising a theoretical well-founded framework for self-adjusting networks which come with provable guarantees and incorporate self–protection mechanisms.
The PI is well-equipped for this project and recently obtained first promising results. As the community is currently re-architecting communication networks, there is a unique opportunity to bridge the gap between theory and practice, and have impact.
Champ scientifique
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineeringautonomous vehicles
- natural sciencesmathematicspure mathematicstopology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networks
Programme(s)
Régime de financement
ERC-COG - Consolidator GrantInstitution d’accueil
10623 Berlin
Allemagne