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Rivière, Etienne
Résultat de la recherche
Efficient and Confidentiality-Preserving Content-Based Publish/Subscribe with Prefiltering
2017, Barazzutti, Raphaël, Felber, Pascal, Mercier, Hugues, Onica, Emanuel, Rivière, Etienne
Edge-centric Computing: Vision and Challenges
2015, López, Pedro, Montresor, Alberto, Epema, Dick, Datta, Anwitaman, Higashino, Teruo, Iamnitchi, Adriana, Barcellos, Marinho, Felber, Pascal, Rivière, Etienne
Lightweight, efficient, robust epidemic dissemination
2013, Matos, Miguel, Schiavoni, Valerio, Felber, Pascal, Oliveira, Rui, Rivière, Etienne
The Velox Transactional Memory Stack
2010, Afek, Yehuda, Drepper, Ulrich, Felber, Pascal, Fetzer, Christof, Gramoli, Vincent, Hohmuth, Michael, Rivière, Etienne, Stenström, Per, Unsal, Osman, Maldonado, Walther, Harmanci, Derin, Marlier, Patrick, Diestelhorst, Stephan, Pohlack, Martin, Cristal, Adrián, Hur, Ibrahim, Dragojevic, Aleksandar, Guerraoui, Rachid, Kapalka, Michal, Tomic, Sasa, Korland, Guy, Shavit, Nir, Nowack, Martin, Riegel, Torvald
Confidentiality-Preserving Publish/Subscribe: A Survey
2016, Onica, Emanuel, Felber, Pascal, Mercier, Hugues, Rivière, Etienne
CoFeed: privacy-preserving Web search recommendation based on collaborative aggregation of interest feedback
2013, Felber, Pascal, Kropf, Peter, Leonini, Lorenzo, Luu, Toan, Rajman, Martin, Rivière, Etienne, Schiavoni, Valerio, Valerio, José
Pulp: An adaptive gossip-based dissemination protocol for multi-source message streams
2012, Felber, Pascal, Kermarrec, Anne-Marie, Leonini, Lorenzo, Rivière, Etienne, Voulgaris, Spyros
Supporting Time-Based QoS Requirements in Software Transactional Memory
2015, Maldonado, Walther, Marlier, Patrick, Felber, Pascal, Lawall, Julia, Muller, Gilles, Rivière, Etienne
Scaling Up Publish/Subscribe Overlays Using Interest Correlation for Link Sharing
2013, Matos, Miguel, Felber, Pascal, Oliveira, Rui, Pereira, José, Rivière, Etienne
Gossip-Based Networking for Internet-Scale Distributed Systems
2011-1-26, Rivière, Etienne, Voulgaris, Spyros
In the era of Internet-scale applications, an increasing number of services are distributed over pools of thousands to millions of networked computers. Along with the obvious advantages in performance and capacity, such a massive scale comes also with challenges. Continuous changes in the system become the norm rather than the exception, either because of inevitable hardware failures or merely due to standard maintenance and upgrading procedures. Rather than trying to impose rigid control on the massive pools of resources, we should equip Internet-scale applications with enough flexibility to work around inevitable faults. In that front, gossiping protocols have emerged as a promising component due to their highly desirable properties: self-healing, self-organizing, symmetric, immensely scalable, and simple. Through visiting a representative set of fundamental gossiping protocols, this paper provides insight on the principles that govern their behavior. By focusing on the rationale and incentives behind gossiping protocols, we introduce the reader to the alternative way of managing massive scale systems through gossiping, and we intrigue her or his interest to delve deeper into the subject by providing an extensive list of pointers.