Data streaming for appliances

Patiño Martinez, Marta and Azqueta Alzúaz, Ainhoa (2019). Data streaming for appliances. In: "9th International Conference on Cloud Computing and Services Science (CLOSER 2019)", 2-4 May 2019, Creta, Grecia. ISBN 978-989-758-365-0. pp. 672-678.


Title: Data streaming for appliances
  • Patiño Martinez, Marta
  • Azqueta Alzúaz, Ainhoa
Item Type: Presentation at Congress or Conference (Article)
Event Title: 9th International Conference on Cloud Computing and Services Science (CLOSER 2019)
Event Dates: 2-4 May 2019
Event Location: Creta, Grecia
Title of Book: ADITCA 2019: Appliances for Data-Intensive and Time Critical Applications I
Date: 2019
ISBN: 978-989-758-365-0
Volume: 1
Freetext Keywords: Data Stream Processing; NUMA aware; Appliances
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Lenguajes y Sistemas Informáticos e Ingeniería del Software
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Nowadays many applications require to analyse the continuous flow of data produced by different data sources before the data is stored. Data streaming engines emerged as a solution for processing data on the fly. At the same time, computer architectures have evolved to systems with several interconnected CPUs and Non Uniform Memory Access (NUMA), where the cost of accessing memory from a core depends on how CPUs are interconnected. This paper presents UPM-CEP, a data streaming engine designed to take advantage of NUMA architectures. The preliminary evaluation using Intel HiBench benchmark shows that NUMA aware deployment improves performance.

Funding Projects

Horizon 2020779747BigDataStackIBM ISRAEL - SCIENCE AND TECHNOLOGY LTDHigh-performance data-centric stack for big data applications and operations
Madrid Regional GovernmentS2013TIC2894Cloud4BigDataUnspecifiedUnspecified
Madrid Regional GovernmentS2018/TCS-4499EDGEDATA-CMUnspecifiedEDGEDATA: una infraestructura para sistemas híbridos altamente descentralizados
Government of SpainTIN2016-80350UnspecifiedUniversidad Politécnica de MadridCLOUDDB: una base de datos ultraescalable, eficiente y altamente disponible
Horizon 2020732051CloudDBApplianceBULL SASEuropean cloud in-memory database appliance with predictable performance for critical applications

More information

Item ID: 56633
DC Identifier:
OAI Identifier:
DOI: 10.5220/0007905906720678
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 23 Oct 2019 07:52
Last Modified: 30 Nov 2022 09:00
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