Title :
A space-saving method for aggregate Top-N flow statistics with high accuracy
Author :
Cao, Xiaoguang ; Feng, Wenzhong ; Dou, Yinan ; Lei, Zhenming ; Yu, Hua
Author_Institution :
Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
In this paper, we propose a new space-saving method for aggregate Top-N flow statistics. Based on the heavy-tailed characteristic in flow statistics, we divide the flow data into two data sets, mainly focus on the non-redundant data set, and restrict the maximum size of redundant data set. By doing this, the total amount of storage space is reduced. To ensure the statistics accuracy, we use the Least Recently Updated elimination algorithm to keep the useful data and discard the data which matters less to the result. The experimental results show that our method has a high accuracy.
Keywords :
data structures; statistical analysis; telecommunication network management; aggregate Top-N flow statistics; heavy-tailed characteristic; least recently updated elimination algorithm; nonredundant data set; space-saving method; storage space; Accuracy; Aggregates; Data structures; IP networks; Indexes; Mice; Monitoring; Hash Table; aggregate Top-N flow statistics; heavy-tailed characteristic; traffic monitoring;
Conference_Titel :
Broadband Network and Multimedia Technology (IC-BNMT), 2011 4th IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-61284-158-8
DOI :
10.1109/ICBNMT.2011.6155966