<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liao, Yongjun</style></author><author><style face="normal" font="default" size="100%">Du, Wei</style></author><author><style face="normal" font="default" size="100%">Leduc, Guy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Lightweight Network Proximity Service Based On Neighborhood Models</style></title><secondary-title><style face="normal" font="default" size="100%">22nd IEEE Symposium on Communications and Vehicular Technology in the Benelux  (SCVT)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Luxembourg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper proposes a network proximity service&amp;nbsp;based on the neighborhood models used in recommender systems.&amp;nbsp;Unlike previous approaches, our service infers network proximity&amp;nbsp;without trying to recover the latency between network nodes. By&amp;nbsp;asking each node to probe a number of landmark nodes which&amp;nbsp;can be servers at Google, Yahoo and Facebook, etc., a simple&amp;nbsp;proximity measure is computed and allows the direct ranking&amp;nbsp;and rating of network nodes by their proximity to a target node.&amp;nbsp;The service is thus lightweight and can be easily deployed in&amp;nbsp;e.g. P2P and CDN applications. Simulations on existing datasets&amp;nbsp;and experiments with a deployment over PlanetLab showed&amp;nbsp;that our service achieves an accurate proximity inference that&amp;nbsp;is comparable to state-of-the-art latency prediction approaches,&amp;nbsp;while being much simpler.&lt;/p&gt;</style></abstract></record></records></xml>