A SPACE-SAVING METHOD FOR AGGREGATE TOP-N FLOW STATISTICS WITH HIGH ACCURACY

摘要：

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.

关键词： traffic monitoring aggregate Top-N flow statistics heavy-tailed characteristic Hash Table

作者: Xiaoguang Cao Wenzhong Feng Yinan Dou Zhenming Lei Hua Yu

作者单位: School of Information and Communication Engineering,Beijing University of Posts and Telecommunications, Beijing 100876, China

会议类型: 国际会议

会议名称: 2011 4th IEEE International Conference on Broadband Network & Multimedia Technology(第四届IEEE宽带网络与多媒体国际会议 4th IEEE IC-BNMT2011)

会议地点: 深圳

会议语种:英文

页码: 407-411

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）