TY - JOUR
T1 - Identifying control and management plane poison message failure by K-nearest neighbor method
AU - Du, Xiaojiang
PY - 2006/6
Y1 - 2006/6
N2 - 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. Also we integrate the k-nearest neighbor method with message filtering approach. We also propose a "probabilistic" k-nearest neighbor method that outputs a probability distribution (rather than the identity) of the poison message. Through extensive simulations, we show that k-nearest neighbor method is very effective in identifying the responsible message type.
AB - 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. Also we integrate the k-nearest neighbor method with message filtering approach. We also propose a "probabilistic" k-nearest neighbor method that outputs a probability distribution (rather than the identity) of the poison message. Through extensive simulations, we show that k-nearest neighbor method is very effective in identifying the responsible message type.
KW - Fault diagnosis
KW - Fault management
KW - K-nearest neighbor method
KW - Poison message failure
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U2 - 10.1007/s10922-006-9027-8
DO - 10.1007/s10922-006-9027-8
M3 - Article
AN - SCOPUS:33745846395
SN - 1064-7570
VL - 14
SP - 243
EP - 259
JO - Journal of Network and Systems Management
JF - Journal of Network and Systems Management
IS - 2
ER -