SEEP: Scalable and elastic event processing

Matteo Migliavacca*, David Eyers, Jean Bacon, Yiannis Papagiannis, Brian Shand, Peter Pietzuch

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Continuous streams of event data are generated in many application domains including financial trading, fraud detection, website analytics and system monitoring. An open challenge in data management is how to analyse and react to large volumes of event data in real-time. As centralised event processing systems reach their computational limits, we need a new class of event processing systems that support deployments at the scale of thousands of machines in a cloud computing setting. In this poster we present SEEP, a novel architecture for event processing that can scale to a large number of machines and is elastic in order to adapt dynamically to workload changes.

Original languageEnglish
Title of host publicationMiddleware'10 Posters and Demos Track, Middleware Posters'10
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventMiddleware'10 Posters and Demos Track, Middleware Posters'10 - Bangalore, India
Duration: 29 Nov 20103 Dec 2010

Publication series

NameMiddleware'10 Posters and Demos Track, Middleware Posters'10

Conference

ConferenceMiddleware'10 Posters and Demos Track, Middleware Posters'10
Country/TerritoryIndia
CityBangalore
Period29/11/103/12/10

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