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REGAL Research team
Large-Scale Distributed Systems and Applications
- Leader : Pierre Sens
- Type : Project team
- Research center(s) : Paris - Rocquencourt
- Field : Networks, Systems and Services, Distributed Computing
- Theme : Distributed Systems and Services
- Université Pierre et Marie Curie (Paris 6), CNRS, Laboratoire d'informatique de Paris 6 (LIP6) (UMR7606)
Team presentation
The main focus of the Regal project team covers a larger part of the whole Computer Systems spectrum. Our topics include Distributed systems, Managed Run-time Environments (MREs, a.k.a. language-level virtual machines) and operating system kernels. We focus on the following objectives:- Distributed algorithms for dynamic and large networks. This objective aims to design distributed algorithms adapted to new large scale or dynamic distributed systems, such as mobile networks, sensor networks, P2P systems, Grids, Cloud environments, and robot networks. We study various key topics of distributed algorithms: mutual exclusion failure detection, data dissemination and data finding in large scale systems self-stabilization and self-* services.
- Management of distributed data. We focus on some emerging architectures: first on distributed hash tables (DHTs), and increasingly on cloud computing architectures. Our research topics include replica placement, responsiveness, load balancing, consistency maintenance, consensus algorithms, and synchronization in such environments.
- Performance and robustness of Systems Software in multicore architectures. Our focus has shifted away from the integration of an MRE into an operating system kernel, and towards the efficient management of system resources at the user level. Issues considered include efficient synchronization and memory management in large-scale multicore architectures. We also focus on the robustness of system software, based on the Coccinelle technology.
Research themes
- Large-scale distributed computing environments, cloud and peer-to-peer computing
- Distributed algorithms for dynamic networks
- Fault Tolerance
- Data replication and consistency
- self-* algorithms
- Runtime support for multicore computing, garbage collection
- System software reliability
International and industrial relations
- Collaboration Federal University of Bahia (CAPES/COFECUB) - Brésil
- Collaboration F. Santa Maria University (CONYCIT) - Chilie
- Collaboration JAIST - Japon
- University of Lisbon (Pessoa)
- Grants: Microsoft, Google
- Projet Europeen Grid4all
- ANR Blanc ABL
- ANR Telecom : SPREADS
- ANR Verso : PROSE, SHAMAN
- ANR Arpège : MyCloud
- FNSN Nu@ge
- ANR Infra : I-JVM
Keywords: Distibuted algorithms and systems Data replication and consistency Fault Tolerance Large scale Virtual Machine and Multi-core Dynamic networks
Research teams of the same theme :
- ACES - Ambient computing and embedded systems
- ADAM - Adaptive Distributed Applications and Middleware
- ARLES - Software architectures and distributed systems
- ASAP - As Scalable As Possible: foundations of large scale dynamic distributed systems
- ASCOLA - Aspect and composition languages
- ATLANMOD - Modeling Technologies for Software Production, Operation, and Evolution
- CIDRE - Confidentialité, Intégrité, Disponibilité et Répartition
- FOCUS - Foundations of Component-based Ubiquitous Systems
- INDES - Secure Diffuse Programming
- LOGNET - Logical Networks: Self-organizing Overlay Networks and Programmable Overlay Computing Systems
- MYRIADS - Design and Implementation of Autonomous Distributed Systems
- OASIS - Active objects, semantics, Internet and security
- PHOENIX - Programming Language Technology For Communication Services
- POPS - System and Networking for Portable Objects Proved to be Safe
- RMOD - Analyses and Languages Constructs for Object-Oriented Application Evolution
- SARDES - System architecture for reflective distributed computing environments
- SCORE - Services and Cooperation
- TRISKELL - Reliable and efficient component based software engineering
Contact
Team leader
Pierre Sens
Tel.: +33 1 44 27 87 65
Secretariat
Tel.: +33 1 39 63 55 52
Inria
Inria.fr
Inria Channel

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