@inproceedings {Col2014,
	title = {Scalable accurate consolidation of passively measured statistical data},
	booktitle = {Passive and Active Measurement (PAM), Extended Abstract},
	year = {2014},
	month = {March},
	address = {Los Angeles, USA},
	abstract = {<p>Passive probes continuously collect a significant amount of traffic vol- ume, and autonomously generate statistics on a large number of metrics. A common statistical output of passive probe is represented by probability mass functions (pmf). The need for consolidation of several pmfs arises in two contexts, namely: (i) whenever a central point collects and aggregates measurement of multiple disjoint vantage points, and (ii) whenever a local measurement processed at a single vantage point needs to be distributed over multiple cores of the same physical probe, in order to cope with growing link capacity. Taking an experimental approach, we study both cases assessing the impact of different consolidation strategies, obtaining general design and tuning guidelines.</p>},
	url = {http://perso.telecom-paristech.fr/~drossi/paper/rossi14pam-a.pdf},
	author = {S. Colabrese and D Rossi and Marco Mellia}
}
