Robust aggregation protocols for large-scale overlay networks

Alberto Montresor, Mark Jelasity, Ozalp Babaoglu

Research output: Contribution to conferencePaper

40 Citations (Scopus)

Abstract

Aggregation refers to a set of functions that provide global information about a distributed system. These functions operate on numeric values distributed over the system and can be used to count network size, determine extremal values and compute averages, products or sums. Aggregation allows important basic functionality to be achieved in fully distributed and peer-to-peer networks. For example, in a monitoring application, some aggregate reaching a specific value may trigger the execution of certain operations; distributed storage systems may need to know the total free space available; load-balancing protocols may benefit from knowing the target average load so as to minimize the transfered load. Building on the simple but efficient idea of anti-entropy aggregation (a scheme based on the anti-entropy epidemic communication model), in this paper we introduce practically applicable robust and adaptive protocols for proactive aggregation, including the calculation of average, product and extremal values. We show how the averaging protocol can be applied to compute further aggregates like sum, variance and the network size. We present theoretical and empirical evidence supporting the robustness of the averaging protocol under different scenarios.

Original languageEnglish
Pages19-28
Number of pages10
Publication statusPublished - Oct 1 2004
Event2004 International Conference on Dependable Systems and Networks - Florence, Italy
Duration: Jun 28 2004Jul 1 2004

Other

Other2004 International Conference on Dependable Systems and Networks
CountryItaly
CityFlorence
Period6/28/047/1/04

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ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Montresor, A., Jelasity, M., & Babaoglu, O. (2004). Robust aggregation protocols for large-scale overlay networks. 19-28. Paper presented at 2004 International Conference on Dependable Systems and Networks, Florence, Italy.