@conference {baquero2009fast,
	title = {Fast estimation of aggregates in unstructured networks},
	booktitle = {Fifth International Conference on Autonomic and Autonomous Systems - ICAS},
	year = {2009},
	month = {April },
	pages = {88{\textendash}93},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Valencia, Spain},
	abstract = {<p>Aggregation of data values plays an important role on distributed computations, in particular over peer-to-peer and sensor networks, as it can provide a summary of some global system property and direct the actions of self-adaptive distributed algorithms. Examples include using estimates of the network size to dimension distributed hash tables or estimates of the average system load to direct loadbalancing. Distributed aggregation using non-idempotent functions, like sums, is not trivial as it is not easy to prevent a given value from being accounted for multiple times; this is especially the case if no centralized algorithms or global identifiers can be used.This paper introduces Extrema Propagation, a probabilistic technique for distributed estimation of the sum of positive real numbers. The technique relies on the exchange of duplicate insensitive messages and can be applied in flood and/or epidemic settings, where multi-path routing occurs; it is tolerant of message loss; it is fast, as the number of message exchange steps equals the diameter; and it is fully distributed, with no single point of failure and the result produced at every node.</p>
},
	attachments = {https://haslab.uminho.pt/sites/default/files/cbm/files/ieeefastfinalicas2009.pdf},
	author = {Carlos Baquero Moreno and Paulo S{\'e}rgio Almeida and Raquel Menezes}
}