%0 Conference Proceedings %T Mignon: A Fast Decentralized Content Consumption Estimation in Large-Scale Distributed Systems %+ As Scalable As Possible: foundations of large scale dynamic distributed systems (ASAP) %+ Laboratoire de Génie Electrique de Grenoble (G2ELab) %A Delbruel, Stéphane %A Frey, Davide %A Taïani, François %< avec comité de lecture %( Lecture Notes in Computer Science %B 16th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (DAIS) %C Heraklion, Greece %Y Márk Jelasity %Y Evangelia Kalyvianaki %I Springer %3 Distributed Applications and Interoperable Systems %V LNCS-9687 %P 32-46 %8 2016-06-06 %D 2016 %R 10.1007/978-3-319-39577-7_3 %K Decentralized systems %K Content consumption %K Estimation %Z Computer Science [cs]/Social and Information Networks [cs.SI]Conference papers %X Although many fully decentralized content distribution systems have been proposed, they often lack key capabilities that make them difficult to deploy and use in practice. In this paper, we look at the particular problem of content consumption prediction, a crucial mechanism in many such systems. We propose a novel, fully decentralized protocol that uses the tags attached by users to on-line content, and exploits the properties of self-organizing kNN overlays to rapidly estimate the potential of a particular content without explicit aggregation. %G English %Z TC 6 %Z WG 6.1 %2 https://inria.hal.science/hal-01301230/document %2 https://inria.hal.science/hal-01301230/file/dais2015.pdf %L hal-01301230 %U https://inria.hal.science/hal-01301230 %~ INSTITUT-TELECOM %~ UNIV-RENNES1 %~ UGA %~ CNRS %~ INRIA %~ UNIV-UBS %~ INSA-RENNES %~ INPG %~ INRIA-RENNES %~ IRISA %~ G2ELAB %~ IRISA_SET %~ INRIA_TEST %~ TESTALAIN1 %~ IFIP-LNCS %~ IFIP %~ CENTRALESUPELEC %~ IRISA-D1 %~ INRIA2 %~ IFIP-TC %~ IFIP-WG %~ IFIP-TC6 %~ IFIP-WG6-1 %~ IFIP-DAIS %~ UR1-HAL %~ UR1-MATH-STIC %~ IFIP-LNCS-9687 %~ UR1-UFR-ISTIC %~ TEST-UNIV-RENNES %~ TEST-UR-CSS %~ UNIV-RENNES %~ INRIA-RENGRE %~ INSTITUTS-TELECOM %~ UGA-COMUE %~ UR1-MATH-NUM