TY - JOUR
T1 - Network failure detection and diagnosis by analyzing Syslog and SNS data
T2 - Applying big data analysis to network operations
AU - Kimura, Tatsuaki
AU - Takeshita, Kei
AU - Toyono, Tsuyoshi
AU - Yokota, Masahiro
AU - Nishimatsu, Ken
AU - Mori, Tatsuya
PY - 2013/11
Y1 - 2013/11
N2 - We introduce two big data analysis methods for diagnosing the causes of network failures and for detecting network failures early Syslogs contain log data generated by the system. We analyzed syslogs and succeeded in detecting the cause of a network failure by automatically learning over 100 million logs without needing any previous knowledge of log data. Analysis of the data of a social networking service (namely, Twitter) enabled us to detect possible network failures by extracting network-failure related tweets, which account for less than 1% of all tweets, in real time and with high accuracy.
AB - We introduce two big data analysis methods for diagnosing the causes of network failures and for detecting network failures early Syslogs contain log data generated by the system. We analyzed syslogs and succeeded in detecting the cause of a network failure by automatically learning over 100 million logs without needing any previous knowledge of log data. Analysis of the data of a social networking service (namely, Twitter) enabled us to detect possible network failures by extracting network-failure related tweets, which account for less than 1% of all tweets, in real time and with high accuracy.
KW - Big data
KW - Network failure detection
KW - Syslog
UR - http://www.scopus.com/inward/record.url?scp=84888622600&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84888622600&partnerID=8YFLogxK
M3 - Review article
AN - SCOPUS:84888622600
SN - 1348-3447
VL - 11
JO - NTT Technical Review
JF - NTT Technical Review
IS - 11
ER -