Name
Title | ||
|---|---|---|
Waterfall Traffic Classification: A Quick Approach to Optimizing Cascade Classifiers. |
Abstract | ||
|---|---|---|
Heterogeneous wireless communication networks, like 4G LTE, transport diverse kinds of IP traffic: voice, video, Internet data, and more. In order to effectively manage such networks, administrators need adequate tools, of which traffic classification is the basis for visualizing, shaping, and filtering the broad streams of IP packets observed nowadays. In this paper, we describe a modular, cascading traffic classification system—the Waterfall architecture—and we extensively describe a novel technique for its optimization—in terms of CPU time, number of errors, and percentage of unrecognized flows. We show how to significantly accelerate the process of exhaustive search for the best performing cascade. We employ five datasets of real Internet transmissions and seven traffic analysis methods to demonstrate that our proposal yields valid results and outperforms a greedy optimizer. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s11277-016-3751-5 | Wireless Personal Communications |
Keywords | Field | DocType |
Network management, Convergent networks, Traffic classification, Machine learning | Traffic classification,Data mining,Traffic analysis,Brute-force search,Computer science,CPU time,Internet traffic engineering,Network packet,Computer network,Internet traffic,The Internet | Journal |
Volume | Issue | ISSN |
96 | 4 | 1572-834X |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pawel Foremski | 1 | 42 | 4.56 |
| C. Callegari | 2 | 98 | 14.23 |
| Michele Pagano | 3 | 198 | 31.51 |