Disparity : scalable anomaly detection for clusters.
In this paper, we describe disparity, a tool that does parallel, scalable anomaly detection for clusters. Disparity uses basic statistical methods and scalable reduction operations to perform data reduction on client nodes and uses these results to locate node anomalies. We discuss the implementation of disparity and present results of its use on a SiCortex SC5832 system.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- DE-AC02-06CH11357
- OSTI ID:
- 1001605
- Report Number(s):
- ANL/MCS/CP-62087; TRN: US201102%%337
- Resource Relation:
- Conference: 37th International Conference on Parallel Processing (ICPP 2008); Sep. 8, 2008 - Sep. 12, 2008; Portland, OR
- Country of Publication:
- United States
- Language:
- ENGLISH
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