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Rivière, Etienne

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Rivière, Etienne
Affiliation principale
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Ancien.ne collaborateur.trice
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https://libra.unine.ch/handle/123456789/288

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  • Publication
    Restriction temporaire
    SAFETHINGS: Data Security by Design in the IoT
    (2017)
    Barbosa, Manuel
    ;
    Mokhtar, Sonia
    ;
    Felber, Pascal 
    ;
    Maia, Francisco
    ;
    Matos, Miguel
    ;
    Oliveira, Rui
    ;
    Rivière, Etienne 
    ;
    Schiavoni, Valerio 
    ;
    Voulgaris, Spyros
  • Publication
    Métadonnées seulement
    DATAFLASKS: epidemic store for massive scale systems
    (: IEEE, 2014-10-6)
    Maia, Francisco
    ;
    Matos, Miguel
    ;
    Vilaça, Ricardo
    ;
    Pereira, José
    ;
    Oliveira, Rui
    ;
    Rivière, Etienne 
    Very large scale distributed systems provide some of the most interesting research challenges while at the same time being increasingly required by nowadays applications. The escalation in the amount of connected devices and data being produced and exchanged, demands new data management systems. Although new data stores are continuously being proposed, they are not suitable for very large scale environments. The high levels of churn and constant dynamics found in very large scale systems demand robust, proactive and unstructured approaches to data management. In this paper we propose a novel data store solely based on epidemic (or gossip-based) protocols. It leverages the capacity of these protocols to provide data persistence guarantees even in highly dynamic, massive scale systems. We provide an open source prototype of the data store and correspondent evaluation.
  • Publication
    Métadonnées seulement
    LayStream: composing standard gossip protocols for live video streaming
    (: IEEE, 2014-9-8)
    Matos, Miguel
    ;
    Schiavoni, Valerio 
    ;
    Rivière, Etienne 
    ;
    Felber, Pascal 
    ;
    Oliveira, Rui
    Gossip-based live streaming is a popular topic, as attested by the vast literature on the subject. Despite the particular merits of each proposal, all need to implement and deal with common challenges such as membership management, topology construction and video packets dissemination. Well-principled gossip-based protocols have been proposed in the literature for each of these aspects. Our goal is to assess the feasibility of building a live streaming system, LAYSTREAM, as a composition of these existing protocols, to deploy the resulting system on real testbeds, and report on lessons learned in the process. Unlike previous evaluations conducted by simulations and considering each protocol independently, we use real deployments. We evaluate protocols both independently and as a layered composition, and unearth specific problems and challenges associated with deployment and composition. We discuss and present solutions for these, such as a novel topology construction mechanism able to cope with the specificities of a large-scale and delay-sensitive environment, but also with requirements from the upper layer. Our implementation and data are openly available to support experimental reproducibility.
  • Publication
    Restriction temporaire
  • Publication
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  • Publication
    Métadonnées seulement
    DATAFLASKS: an epidemic dependable key-value substrate
    (: IEEE, 2013-6-30)
    Maia, Francisco
    ;
    Matos, Miguel
    ;
    Vilaça, Ricardo
    ;
    Pereira, José
    ;
    Oliveira, Rui
    ;
    Rivière, Etienne 
    Recently, tuple-stores have become pivotal structures in many information systems. Their ability to handle large datasets makes them important in an era with unprecedented amounts of data being produced and exchanged. However, these tuple-stores typically rely on structured peer-to-peer protocols which assume moderately stable environments. Such assumption does not always hold for very large scale systems sized in the scale of thousands of machines. In this paper we present a novel approach to the design of a tuple-store. Our approach follows a stratified design based on an unstructured substrate. We focus on this substrate and how the use of epidemic protocols allow reaching high dependability and scalability.
  • Publication
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  • Publication
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  • Publication
    Métadonnées seulement
    Slead: low-memory steady distributed systems slicing
    (: Springer, 2012-6-1)
    Maia, Francisco
    ;
    Matos, Miguel
    ;
    Rivière, Etienne 
    ;
    Oliveira, Rui
    Slicing a large-scale distributed system is the process of autonomously partitioning its nodes into k groups, named slices. Slicing is associated to an order on node-specific criteria, such as available storage, uptime, or bandwidth. Each slice corresponds to the nodes between two quantiles in a virtual ranking according to the criteria. For instance, a system can be split in three groups, one with nodes with the lowest uptimes, one with nodes with the highest uptimes, and one in the middle. Such a partitioning can be used by applications to assign different tasks to different groups of nodes, e.g., assigning critical tasks to the more powerful or stable nodes and less critical tasks to other slices. Assigning a slice to each node in a large-scale distributed system, where no global knowledge of nodes’ criteria exists, is not trivial. Recently, much research effort was dedicated to guaranteeing a fast and correct convergence in comparison to a global sort of the nodes. Unfortunately, state-of-the-art slicing protocols exhibit flaws that preclude their application in real scenarios, in particular with respect to cost and stability. In this paper, we identify steadiness issues where nodes in a slice border constantly exchange slice and large memory requirements for adequate convergence, and provide practical solutions for the two. Our solutions are generic and can be applied to two different state-of-the-art slicing protocols with little effort and while preserving the desirable properties of each. The effectiveness of the proposed solutions is extensively studied in several simulated experiments.