InteMon: Continuous mining of sensor data in large-scale self-* infrastructures

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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)38-44
Number of pages7
JournalOperating Systems Review (ACM)
Volume40
Issue number3
DOIs
StatePublished - Jul 1 2006
Externally publishedYes

ASJC Scopus subject areas

  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications

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