Antonio Nucci - Burlingame CA, US Su Chen - Somerset NJ, US
Assignee:
Narus, Inc. - Sunnyvale CA
International Classification:
H04J 3/18
US Classification:
370477
Abstract:
An important component of network monitoring is to collect traffic data which is a bottleneck due to large data size. We introduce a new table compression method called “Group Compression” to address this problem. This method uses a small training set to learn the relationship among columns and group them; the result is a “compression plan”. Based on this plan, each group is compressed separately. This method can reduce the compressed size to 60%-70% of the IP flow logs compressed by GZIP.