A big data platform for large scale event processing

Gulisano, Vincenzo Massimiliano and Jiménez-Peris, Ricardo and Patiño-Martínez, M. and Soriente, Claudio and Valduriez, Patrick (2011). A big data platform for large scale event processing. "Ercim News" (n. 89); pp. 32-33. ISSN 0926-4981.

Description

Title: A big data platform for large scale event processing
Author/s:
  • Gulisano, Vincenzo Massimiliano
  • Jiménez-Peris, Ricardo
  • Patiño-Martínez, M.
  • Soriente, Claudio
  • Valduriez, Patrick
Item Type: Article
Título de Revista/Publicación: Ercim News
Date: 2011
ISSN: 0926-4981
Subjects:
Faculty: Facultad de Informática (UPM)
Department: Lenguajes y Sistemas Informáticos e Ingeniería del Software
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

To date, big data applications have focused on the store-and-process paradigm. In this paper we describe an initiative to deal with big data applications for continuous streams of events. In many emerging applications, the volume of data being streamed is so large that the traditional ‘store-then-process’ paradigm is either not suitable or too inefficient. Moreover, soft-real time requirements might severely limit the engineering solutions. Many scenarios fit this description. In network security for cloud data centres, for instance, very high volumes of IP packets and events from sensors at firewalls, network switches and routers and servers need to be analyzed and should detect attacks in minimal time, in order to limit the effect of the malicious activity over the IT infrastructure. Similarly, in the fraud department of a credit card company, payment requests should be processed online and need to be processed as quickly as possible in order to provide meaningful results in real-time. An ideal system would detect fraud during the authorization process that lasts hundreds of milliseconds and deny the payment authorization, minimizing the damage to the user and the credit card company.

More information

Item ID: 13648
DC Identifier: http://oa.upm.es/13648/
OAI Identifier: oai:oa.upm.es:13648
Deposited by: Memoria Investigacion
Deposited on: 25 Feb 2013 08:36
Last Modified: 21 Apr 2016 12:58
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