Towards Scalable Critical Alert Mining

author: Bo Zong, University of California, Santa Barbara
published: Oct. 7, 2014,   recorded: August 2014,   views: 1546


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


Performance monitor software for data centers typically generates a great number of alert sequences. These alert sequences indicate abnormal network events. Given a set of observed alert sequences, it is important to identify the most critical alerts that are potentially the causes of others. While the need for mining critical alerts over large scale alert sequences is evident, most alert analysis techniques stop at modeling and mining the causal relations among the alerts.

This paper studies the critical alert mining problem: Given a set of alert sequences, we aim to find a set of k critical alerts such that the number of alerts potentially triggered by them is maximized. We show that the problem is intractable; therefore, we resort to approximation and heuristic algorithms. First, we develop an approximation algorithm that obtains a near-optimal alert set in quadratic time, and propose pruning techniques to improve its runtime performance. Moreover, we show a faster approximation exists, when the alerts follow certain causal structure. Second, we propose two fast heuristic algorithms based on tree sampling techniques. On real-life data, these algorithms identify a critical alert from up to 270,000 mined causal relations in 5 seconds; meanwhile, they preserve more than 80% of solution quality, and are up to 5,000 times faster than their approximation counterparts.

See Also:

Download slides icon Download slides: kdd2014_zong_alert_mining_01.pdf (791.6┬áKB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: