@inproceedings {Yon2015,
	title = {A Lightweight Network Proximity Service Based On Neighborhood Models},
	booktitle = {22nd IEEE Symposium on Communications and Vehicular Technology in the Benelux  (SCVT)},
	year = {2015},
	month = {11/2015},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Luxembourg},
	abstract = {<p>This paper proposes a network proximity service\&nbsp;based on the neighborhood models used in recommender systems.\&nbsp;Unlike previous approaches, our service infers network proximity\&nbsp;without trying to recover the latency between network nodes. By\&nbsp;asking each node to probe a number of landmark nodes which\&nbsp;can be servers at Google, Yahoo and Facebook, etc., a simple\&nbsp;proximity measure is computed and allows the direct ranking\&nbsp;and rating of network nodes by their proximity to a target node.\&nbsp;The service is thus lightweight and can be easily deployed in\&nbsp;e.g. P2P and CDN applications. Simulations on existing datasets\&nbsp;and experiments with a deployment over PlanetLab showed\&nbsp;that our service achieves an accurate proximity inference that\&nbsp;is comparable to state-of-the-art latency prediction approaches,\&nbsp;while being much simpler.</p>},
	author = {Liao, Yongjun and Du, Wei and Leduc, Guy}
}
