PDL Abstract

InteMon: Continuous Mining of Sensor Data in Large-scale Self-* Infrastructures

ACM SIGOPS Operating Systems Review. Vol 40 Issue 3. July, 2006. ACM Press.

Evan Hoke, Jimeng Sun, John D. Strunk*, Gregory R. Ganger*, Christos Faloutsos

School of Computer Science
*Dept. Electrical and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA 15213

Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon, a prototype monitoring and mining system for data centers. It uses the SNMP protocol to monitor a new data center at Carnegie Mellon. It stores the monitoring data in a MySQL database, allowing visualization of the time-series data using a JSP web-based frontend interface for system administrators. What sets InteMon apart from other cluster monitoring systems is its ability to automatically analyze correlations in the monitoring data in real time and alert administrators of potential anomalies. It uses efficient, state of the art stream mining methods to report broken correlations among input streams. It also uses these methods to intelligently compress historical data and avoid the need for administrators to configure threshold-based monitoring bands.

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