Anomaly Detection Algorithm of Data Center Network Based on LSDB
Xu Gang, Wang Zhan, Zang Dawei, An Xuejun
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At present, due to network attack, network configuration and etc, routing table changes frequently in data center network. However, because of the lack of effective monitoring software and routing anomalies, route flapping is difficult to find and locate the fault. When data center network failure occurs, we can’t locate the problem and it will lead to extend the time to repair, degrade the user experience and reduce operating incoming and etc. This paper analyzes the current mainstream data center network architecture, communication protocol and routing calculation principle, then we proposes LSAP which is an data center network anomaly detection method based on the link state database. According to the comparison of snapshots in LSDB and RIB, it can find abnormal link, abnormal routing and locate the fault by collecting link state database, using the improved routing algorithm to calculate the whole network routing. Based on the large data analysis platform, LSAP can compute routing table in real time, achieve processing millions of routing information in seconds and meet the requirements of the current data center for the analysis rate. Through the deployment of the trial in the data center, LSAP can quickly restore routing table, find the topology change and make statistical analysis of all the changes in the route. It has little change to the network, and doesn’t affect the stability of the network, so it applies to the data center with higher stability requirements.