Abstract
Poison message failure is a mechanism that has been responsible for large scale failures in both telecommunications and IP networks. The poison message failure can propagate in the network and cause unstable network In this paper, we apply machine learning, data mining technique in network fault management area. We use k-nearest neighbor method to identify the poison message failure. We also propose a "probabilistic" k-nearest neighbor method which outputs a probability distribution about the poison message. Through extensive simulations, we show that k-nearest neighbor method is very effective in identifying the responsible message type.
Original language | English |
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Pages | 2113-2117 |
Number of pages | 5 |
State | Published - 2004 |
Event | GLOBECOM'04 - IEEE Global Telecommunications Conference - Dallas, TX, United States Duration: 29 Nov 2004 → 3 Dec 2004 |
Conference
Conference | GLOBECOM'04 - IEEE Global Telecommunications Conference |
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Country/Territory | United States |
City | Dallas, TX |
Period | 29/11/04 → 3/12/04 |