Skip to Main content Skip to Navigation
Journal articles

Tracking Freeriders in Gossip-Based Content Dissemination Systems

Rachid Guerraoui 1 Kévin Huguenin 2 Anne-Marie Kermarrec 3 Maxime Monod 1 Swagatika Prusty 4 Aline Roumy 5
1 LPD
LPD - Distributed Programming Laboratory, EPFL - Ecole Polytechnique Fédérale de Lausanne
2 LCA1
LCA - Laboratory for Computer Communications and Applications, EPFL - Ecole Polytechnique Fédérale de Lausanne
3 ASAP - As Scalable As Possible: foundations of large scale dynamic distributed systems
IRISA-D1 - SYSTÈMES LARGE ÉCHELLE, Inria Rennes – Bretagne Atlantique
5 Sirocco - Analysis representation, compression and communication of visual data
IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE, Inria Rennes – Bretagne Atlantique
Abstract : Gossip-based protocols have proven very efficient for disseminating high-bandwidth content such as video streams in a peer-to-peer fashion. However, for the protocols to work, nodes are required to collaborate by devoting a fraction of their upload bandwidth, a scarce resource for some of them, to forward the content they receive to other nodes. Consequently, such protocols suffer from freeriding, a common phenomenon on the Internet, which consists in selfishly benefiting from the system without contributing its fair share. Due to the dynamic nature and the inherent randomness of gossip protocols and to the high scalability requirements of video streaming systems, detecting freeriders is a difficult challenge. This paper presents LiFTinG , the first protocol for detecting freeriders, including colluding ones, in gossip-based content dissemination systems with asymmetric data exchanges. In addition, LiFTinG is still able to detect freeriders when network coding, a widely used technique to improve the efficiency of content dissemination, is used. LiFTinG relies on nodes to track abnormal behavior by cross-checking the history of their previous interactions and exploits the fact that nodes pick neighbors at random to prevent colluding nodes from mutually covering up their bad actions. We present a methodology for setting the parameters of LiFTinG to their optimal value, based on a theoretical analysis and we quantify theoretically the performance of LiFTinG . We derive, based on simulations, the optimal strategy of freeriders by taking into account, through a utility function, the benefit of freeriding and the probability of being detected. In addition to these simulations, we report on the deployment of LiFTinG on PlanetLab. In a 300-node system, where a stream of 674kbps is broadcasted, LiFTinG incurs a maximum overhead of only 8% and provides good detection results: For instance, with 10% of freeriders decreasing their contribution by up to 30%, LiFTinG detects 86% of the freeriders after only 30 seconds and wrongfully expels only a few honest nodes (most of them actually being buggy).
Document type :
Journal articles
Complete list of metadatas

Cited literature [53 references]  Display  Hide  Download

https://hal.inria.fr/hal-00941107
Contributor : Kévin Huguenin <>
Submitted on : Monday, February 3, 2014 - 1:39:59 PM
Last modification on : Wednesday, December 18, 2019 - 5:17:20 PM
Long-term archiving on: : Sunday, May 4, 2014 - 4:51:52 AM

File

Guerraoui14COMNET.pdf
Files produced by the author(s)

Identifiers

Citation

Rachid Guerraoui, Kévin Huguenin, Anne-Marie Kermarrec, Maxime Monod, Swagatika Prusty, et al.. Tracking Freeriders in Gossip-Based Content Dissemination Systems. Computer Networks, Elsevier, 2014, 64, pp.322-338. ⟨10.1016/j.comnet.2014.02.023⟩. ⟨hal-00941107⟩

Share

Metrics

Record views

1353

Files downloads

448