IEICE TRANSACTIONS on Communications
Stream Mining for Network Management
Summary :
Network management is an important issue in maintaining the Internet as an important social infrastructure. Finding excessive consumption of network bandwidth caused by P2P mass flows is especially important. Finding Internet viruses is also an important security issue. Although stream mining techniques seem to be promising techniques to find P2P and Internet viruses, vast network flows prevent the simple application of such techniques. A mining technique which works well with extremely limited memory is required. Also it should have a real-time analysis capability. In this paper, we propose a cache based mining method to realize such a technique. By analyzing the characteristics of the proposed method with real Internet backbone flow data, we show the advantages of the proposed method, i.e. less memory consumption while realizing real-time analysis capability. We also show the fact that we can use the proposed method to find mass flow information from Internet backbone flow data.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E89-B No.6 pp.1774-1780
- Publication Date
- 2006/06/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1093/ietcom/e89-b.6.1774
- Type of Manuscript
- PAPER
- Category
- Network Management/Operation
Authors
Keyword
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Kenichi YOSHIDA, Satoshi KATSUNO, Shigehiro ANO, Katsuyuki YAMAZAKI, Masato TSURU, "Stream Mining for Network Management" in IEICE TRANSACTIONS on Communications,
vol. E89-B, no. 6, pp. 1774-1780, June 2006, doi: 10.1093/ietcom/e89-b.6.1774.
Abstract: Network management is an important issue in maintaining the Internet as an important social infrastructure. Finding excessive consumption of network bandwidth caused by P2P mass flows is especially important. Finding Internet viruses is also an important security issue. Although stream mining techniques seem to be promising techniques to find P2P and Internet viruses, vast network flows prevent the simple application of such techniques. A mining technique which works well with extremely limited memory is required. Also it should have a real-time analysis capability. In this paper, we propose a cache based mining method to realize such a technique. By analyzing the characteristics of the proposed method with real Internet backbone flow data, we show the advantages of the proposed method, i.e. less memory consumption while realizing real-time analysis capability. We also show the fact that we can use the proposed method to find mass flow information from Internet backbone flow data.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e89-b.6.1774/_p
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@ARTICLE{e89-b_6_1774,
author={Kenichi YOSHIDA, Satoshi KATSUNO, Shigehiro ANO, Katsuyuki YAMAZAKI, Masato TSURU, },
journal={IEICE TRANSACTIONS on Communications},
title={Stream Mining for Network Management},
year={2006},
volume={E89-B},
number={6},
pages={1774-1780},
abstract={Network management is an important issue in maintaining the Internet as an important social infrastructure. Finding excessive consumption of network bandwidth caused by P2P mass flows is especially important. Finding Internet viruses is also an important security issue. Although stream mining techniques seem to be promising techniques to find P2P and Internet viruses, vast network flows prevent the simple application of such techniques. A mining technique which works well with extremely limited memory is required. Also it should have a real-time analysis capability. In this paper, we propose a cache based mining method to realize such a technique. By analyzing the characteristics of the proposed method with real Internet backbone flow data, we show the advantages of the proposed method, i.e. less memory consumption while realizing real-time analysis capability. We also show the fact that we can use the proposed method to find mass flow information from Internet backbone flow data.},
keywords={},
doi={10.1093/ietcom/e89-b.6.1774},
ISSN={1745-1345},
month={June},}
Copy
TY - JOUR
TI - Stream Mining for Network Management
T2 - IEICE TRANSACTIONS on Communications
SP - 1774
EP - 1780
AU - Kenichi YOSHIDA
AU - Satoshi KATSUNO
AU - Shigehiro ANO
AU - Katsuyuki YAMAZAKI
AU - Masato TSURU
PY - 2006
DO - 10.1093/ietcom/e89-b.6.1774
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E89-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2006
AB - Network management is an important issue in maintaining the Internet as an important social infrastructure. Finding excessive consumption of network bandwidth caused by P2P mass flows is especially important. Finding Internet viruses is also an important security issue. Although stream mining techniques seem to be promising techniques to find P2P and Internet viruses, vast network flows prevent the simple application of such techniques. A mining technique which works well with extremely limited memory is required. Also it should have a real-time analysis capability. In this paper, we propose a cache based mining method to realize such a technique. By analyzing the characteristics of the proposed method with real Internet backbone flow data, we show the advantages of the proposed method, i.e. less memory consumption while realizing real-time analysis capability. We also show the fact that we can use the proposed method to find mass flow information from Internet backbone flow data.
ER -
English
