Efficient Control of False Negative and False Positive Errors with Separate Adaptive Thresholds

Component level performance thresholds are widely used as a basic means for performance management. As the complexity of managed applications increases, manual threshold maintenance becomes a difficult task. Complexity arises from having a large number of application components and their operational...

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Bibliographic Details
Published in:IEEE eTransactions on network and service management 2011-06, Vol.8 (2), p.128-140
Main Authors: Breitgand, David, Goldstein, Maayan, Henis, Ealan, Shehory, Onn
Format: Article
Language:English
Subjects:
adaptive algorithm
adaptive control
Algorithms
Complexity
Equations
Error analysis
Errors
Logistics
Management
Mathematical model
Mathematical models
Measurement
Monitoring
Networks
performance analysis
Performance management
Stochastic processes
Studies
System performance
Thresholds
Tuning
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Summary:Component level performance thresholds are widely used as a basic means for performance management. As the complexity of managed applications increases, manual threshold maintenance becomes a difficult task. Complexity arises from having a large number of application components and their operational metrics, dynamically changing workloads, and compound relationships between application components. To alleviate this problem, we advocate that component level thresholds should be computed, managed and optimized automatically and autonomously. To this end, we have designed and implemented a performance threshold management application that automatically and dynamically computes two separate component level thresholds: one for controlling Type I errors and another for controlling Type II errors. Our solution additionally facilitates metric selection thus minimizing management overheads. We present the theoretical foundation for this autonomic threshold management application, describe a specific algorithm and its implementation, and evaluate it using real-life scenarios and production data sets. As our present study shows, with proper parameter tuning, our on-line dynamic solution is capable of nearly optimal performance thresholds calculation.
ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2011.020111.00055