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 |
|---|---|
| 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 |
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Keywords
- Bayes' theorem
- Flow statistics
- Measurement
- Packet sampling
- The elephant and mice phenomenon
ASJC Scopus subject areas
- Engineering(all)
Cite this
Identifying elephant flows through periodically sampled packets. / Mori, Tatsuya; Uchida, Masato; Kawahara, Ryoichi; Pan, Jianping; Goto, Shigeki.
Proceedings of the 2004 ACM SIGCOMM Internet Measurement Conference, IMC 2004. 2004. p. 115-120.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
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 -