Publication | Closed Access
Real-time analysis of NetFlow data for generating network traffic statistics using Apache Spark
12
Citations
3
References
2016
Year
Unknown Venue
Cluster ComputingInternet Traffic AnalysisEngineeringNetwork AnalysisApache SparkData Streaming ArchitectureStreaming DataReal-time AnalyticsData ScienceData MiningManagementData IntegrationData ManagementStream ProcessingStreaming EngineComputer ScienceData Stream ManagementTraffic MonitoringNetwork Traffic MonitoringNetwork Traffic StatisticsReal-time AnalysisStream Processing SystemEdge ComputingCloud ComputingNetwork Traffic MeasurementBig Data
In this paper, we present a framework for the real-time generation of network traffic statistics on Apache Spark Streaming, a modern distributed stream processing system. Our previous results showed that stream processing systems provide enough throughput to process a large volume of NetFlow data and hence they are suitable for network traffic monitoring. This paper describes the integration of Apache Spark Streaming into a current network monitoring architecture. We prove that it is possible to implement the same basic methods for NetFlow data analysis in the stream processing framework as in the traditional ones. Moreover, our stream processing implementation discovers new information which is not available when using traditional network monitoring approaches.
| Year | Citations | |
|---|---|---|
Page 1
Page 1