### Abstract

Identifying elephant flows is very important in developing effective and efficient traffic engineering schemes. In addition, obtaining the statistics of these flows is also very useful for network operation and management. On the other hand, with the rapid growth of link speed in recent years, packet sampling has become a very attractive and scalable means to measure flow statistics; however, it also makes identifying elephant flows become much more difficult. Based on Bayes' theorem, this paper develops techniques and schemes to identify elephant flows in periodically sampled packets. We show that our basic framework is very flexible in making appropriate trade-offs between false positives (misidentified flows) and false negatives (missed elephant flows) with regard to a given sampling frequency. We further validate and evaluate our approach by using some publicly available traces. Our schemes are generic and require no per-packet processing; hence, they allow a very cost-effective implementation for being deployed in large-scale high-speed networks.

Original language | English |
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Title of host publication | Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004 |

Pages | 115-120 |

Number of pages | 6 |

Publication status | Published - 2004 |

Event | Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004 - Taormina Duration: 2004 Oct 25 → 2004 Oct 27 |

### Other

Other | Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004 |
---|---|

City | Taormina |

Period | 04/10/25 → 04/10/27 |

### Fingerprint

### Keywords

- Bayes' theorem
- Flow statistics
- Measurement
- Packet sampling
- The elephant and mice phenomenon

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004*(pp. 115-120)

**Identifying elephant flows through periodically sampled packets.** / Mori, Tatsuya; Uchida, Masato; Kawahara, Ryoichi; Pan, Jianping; Goto, Shigeki.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004.*pp. 115-120, Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004, Taormina, 04/10/25.

}

TY - GEN

T1 - Identifying elephant flows through periodically sampled packets

AU - Mori, Tatsuya

AU - Uchida, Masato

AU - Kawahara, Ryoichi

AU - Pan, Jianping

AU - Goto, Shigeki

PY - 2004

Y1 - 2004

N2 - Identifying elephant flows is very important in developing effective and efficient traffic engineering schemes. In addition, obtaining the statistics of these flows is also very useful for network operation and management. On the other hand, with the rapid growth of link speed in recent years, packet sampling has become a very attractive and scalable means to measure flow statistics; however, it also makes identifying elephant flows become much more difficult. Based on Bayes' theorem, this paper develops techniques and schemes to identify elephant flows in periodically sampled packets. We show that our basic framework is very flexible in making appropriate trade-offs between false positives (misidentified flows) and false negatives (missed elephant flows) with regard to a given sampling frequency. We further validate and evaluate our approach by using some publicly available traces. Our schemes are generic and require no per-packet processing; hence, they allow a very cost-effective implementation for being deployed in large-scale high-speed networks.

AB - Identifying elephant flows is very important in developing effective and efficient traffic engineering schemes. In addition, obtaining the statistics of these flows is also very useful for network operation and management. On the other hand, with the rapid growth of link speed in recent years, packet sampling has become a very attractive and scalable means to measure flow statistics; however, it also makes identifying elephant flows become much more difficult. Based on Bayes' theorem, this paper develops techniques and schemes to identify elephant flows in periodically sampled packets. We show that our basic framework is very flexible in making appropriate trade-offs between false positives (misidentified flows) and false negatives (missed elephant flows) with regard to a given sampling frequency. We further validate and evaluate our approach by using some publicly available traces. Our schemes are generic and require no per-packet processing; hence, they allow a very cost-effective implementation for being deployed in large-scale high-speed networks.

KW - Bayes' theorem

KW - Flow statistics

KW - Measurement

KW - Packet sampling

KW - The elephant and mice phenomenon

UR - http://www.scopus.com/inward/record.url?scp=14944376803&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=14944376803&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:14944376803

SN - 1581138210

SN - 9781581138214

SP - 115

EP - 120

BT - Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004

ER -