On the design and performance evaluation of automatic traffic report generation systems with huge data volumes
Fecha
2018Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Impacto
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10.1002/nem.2044
Resumen
In this paper we analyze the performance issues involved in the generation of automated
traffic reports for large IT infrastructures. Such reports allow the IT manager
to proactively detect possible abnormal situations and roll out the corresponding corrective
actions. With the ever-increasing bandwidth of current networks, the design
of automated traffic report generation systems is very cha ...
[++]
In this paper we analyze the performance issues involved in the generation of automated
traffic reports for large IT infrastructures. Such reports allow the IT manager
to proactively detect possible abnormal situations and roll out the corresponding corrective
actions. With the ever-increasing bandwidth of current networks, the design
of automated traffic report generation systems is very challenging. In a first step, the
huge volumes of collected traffic are transformed into enriched flow records obtained
from diverse collectors and dissectors. Then, such flow records, along with time
series obtained from the raw traffic, are further processed to produce a usable report.
As will be shown, the data volume in flow records turns out to be very large as
well and requires careful selection of the Key Performance Indicators (KPIs) to be
included in the report. In this regard, we discuss the use of high-level languages versus
low-level approaches, in terms of speed and versatility. Furthermore, our design
approach is targeted for rapid development in commodity hardware, which is essential
to cost-effectively tackle demanding traffic analysis scenarios. Actually, the paper
shows feasibility of delivering a large number of KPIs, as will be detailed later,
for several TBytes of traffic per day using a commodity hardware architecture and
high-level languages. [--]
Materias
Traffic analysis,
Network management,
Automatic reports
Editor
Wiley
Publicado en
International Journal of Network Management, vol. 28, issue 6, november/december 2018 e2044
Departamento
Universidad Pública de Navarra. Departamento de Ingeniería Eléctrica, Electrónica y de Comunicación /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza Saila
Versión del editor
Entidades Financiadoras
This work has been partially supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund under the projects TRÁFICA (MINECO/FEDER TEC2015‐69417‐C2‐1‐R) and Procesado Inteligente de Tráfico (MINECO/FEDER TEC2015‐69417‐C2‐2‐R). The authors also thank the Spanish Ministry of Education, Culture and Sports for a collaboration grant.