Fast estimation of aggregates in unstructured networks

Citation:
Moreno CB, Almeida PS, Menezes R.  2009.  Fast estimation of aggregates in unstructured networks. Fifth International Conference on Autonomic and Autonomous Systems - ICAS. :88–93.

Date Presented:

April

Abstract:

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.

Citation Key:

baquero2009fast

DOI:

10.1109/ICAS.2009.31

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