Growing demand for pro-active abilities in network management requires performance monitoring agents not only to be able to monitor the anomalies, but also to predict future occurrences. Recent research in this area would usually apply a neural network algorithm on raw SNMP or NetFlow data to obtain the knowledge about the patterns in performance data. The results are not always satisfactory due to highly unpredictable nature of cross-traffic in the network. This paper attempts to improve the prediction quality by using data obtained from end-to-end probing. The results prove higher resilience to cross-traffic interference and better pattern recognition.
|Title of host publication||First IEEE and IFIP International Conference in Central Asia on Internet, 2005|
|Publication status||Published - 2005|
|Event||First IEEE and IFIP International Conference in Central Asia on Internet, 2005 - Bishkek|
Duration: 2005 Sep 26 → 2005 Sep 28
|Other||First IEEE and IFIP International Conference in Central Asia on Internet, 2005|
|Period||05/9/26 → 05/9/28|
ASJC Scopus subject areas