Section: Partnerships and Cooperations

International Initiatives

ARMADA

• Title: hARnessing MAssive DAta flows

• International Partner (Institution - Laboratory - Researcher):

  • Universidad Tecnica Federico Santa Maria (Chile) - Department of Computer Science (Department of Comput) - Xavier Bonnaire

• Start year: 2014

• See also: http://web.inria-armada.org

• The ARMADA project aims at designing and implementing a reliable framework for the management and processing of massive dynamic dataflows. The project is two-pronged: fault-tolerant middleware support for processing massive continuous input, and a redundant storage service for mutable data on a massive scale.

• Title: Application dependent intrusion (byzantine) detection in Dynamic cloud systems

• International Partner (Institution - Laboratory - Researcher):

  • Technion Haifa - Prof. Roy Friedman

• Duration: 2014–2015

• The goal of this project is to study the ability to tolerate Byzantine failures in dynamic environments. The Byzantine model allows arbitrary behaviour of a certain fraction of nodes. Our goal is to provide both a theoretical framework and performance evaluation to tolerate Byzantine behaviour in dynamic distributed environments. We consider "bag of tasks" (BoT) applications characterized by trivial parallelism where a large computational problem is broken into a large number of independent tasks. These tasks can be spread on commodity hardware and operating systems. We target different executions environments: (1) Clouds: tasks are submitted to virtual machines hosted at cloud providers, (2) Desktop grid: tasks are submitted to federate large pool of donated machines hosted at user home, (3) Hybrid cloud: combining both cloud and desktop nodes.

• Title: Autonomic and Scalable Algorithms for Building Resilient Distributed Systems

• International Partner (Institution - Laboratory - Researcher):

  • Universida de Federal do Paraná (UFPR), Brazil, Prof. Elias Duarte

• Duration: 2015–2017

• In the context of autonomic computing systems that detect and diagnose problems, self-adapting themselves, the VCube (Virtual Cube), proposed by Prof. Elias Duarte , is a distributed diagnosis algorithm that organizes the system nodes on a virtual hypercube topology. VCube has logarithmic properties: when all nodes are fault-free, processes are virtually connected to form a perfect hypercube; as soon as one or more failures are detected, links are automatically reconnected to remove the faulty nodes and the resulting topology, connecting only fault-free nodes, keeps the logarithmic properties. The goal of this project is to exploit the autonomic and logarithmic properties of the VCube by proposing self-adapting and self-configurable services.