Scaling Out the Performance of Service Monitoring Applications with BlockMon
To cope with real-time data analysis as the amount of data being exchanged over the network increases, an idea is to re-design algorithms originally implemented on the monitoring probe to work in a distributed manner over a stream-processing platform. In this paper we show preliminary performance analysis of a Twitter trending algorithm when running over BlockMon, an open-source monitoring platform which we extended to run distributed data-analytics algorithms: we show that it performs up to 23.5x and 34.2x faster on BlockMon than on Storm and Apache S4 respectively, two emerging stream-processing platforms.
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