LiFTinG: Lightweight Freerider-Tracking in Gossip

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Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_D3DF89C456DF
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Titre
LiFTinG: Lightweight Freerider-Tracking in Gossip
Titre de la conférence
Proceedings of the 11th ACM/IFIP/USENIX International Middleware Conference (MIDDLEWARE)
Auteur⸱e⸱s
Guerraoui R., Huguenin K., Kermarrec A.-M., Monod M., Prusty S.
Editeur
Springer
Adresse
Bangalore, India
ISBN
978-3-642-16954-0
978-3-642-16955-7
ISSN
0302-9743
1611-3349
Statut éditorial
Publié
Date de publication
2010
Peer-reviewed
Oui
Volume
6452
Série
Lecture Notes in Computer Science
Pages
313-333
Langue
anglais
Résumé
This paper presents LiFTinG, the first protocol to detect freeriders, including colluding ones, in gossip-based content dissemination systems with asymmetric data exchanges. LiFTinG relies on nodes tracking abnormal behaviors by cross-checking the history of their previous interactions, and exploits the fact that nodes pick neighbors at random to prevent colluding nodes from covering up each others' bad actions.
We present a methodology to set the parameters of LiFTinG based on a theoretical analysis. In addition to simulations, we report on the deployment of LiFTinG on Planet Lab. In a 300-node system, where a stream of 674 kbps is broadcast, LiFTinG incurs a maximum overhead of only 8% while providing good results: for instance, with 10% of freeriders decreasing their contribution by 30%, LiFTinG detects 86% of the freeriders after only 30 seconds and wrongfully expels only a few honest nodes.
Web of science
Open Access
Oui
Création de la notice
01/12/2016 10:48
Dernière modification de la notice
20/08/2019 15:53
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