Title :
Sampling method based on HBF for recording more flows
Author :
Lei Bai ; Xiaoxin Guo
Author_Institution :
Comput. Coll., North China Inst. of Sci. & Technol., Yanjiao, China
Abstract :
For the limit of false positives probability in Bloom Filter (BF), this paper proposed a novel mechanism based on Hierarchy Bloom Filter (HBF) for recording network flows statistic. By extending the standard structure of Bloom Filter to multi-layer with the false positives probability which predefined each layer, the mechanism could not only record more flows, but also adapt dynamically when the number of flows rapidly rising. The experimental simulation results shown that compared with a single layer of Bloom Filter, the algorithm can significantly improve the accuracy of recording flows information.
Keywords :
data structures; sampling methods; HBF; false positives probability; flows information; hierarchy bloom filter; network flows statistic; sampling method; Algorithm design and analysis; Error probability; Filtering algorithms; Information filters; Standards; Telecommunication traffic; Bloom filter; False Positives; Flows; Sample; Traffic measurement;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location :
Dalian
DOI :
10.1109/ICCSNT.2013.6967258