Workload Characterization Techniques
This lecture covers the following topics:
- Terminology
- Components and Parameter Selection
- Workload Characterization Techniques
- Averaging
- Case Study: Program Usage in Educational Environments
- Characteristics of an Average Editing Session
- Single Parameter Histograms
- Multi-parameter Histograms
- Principal Component Analysis
- Finding Principal Factors
- Principal Component Example
- Markov Models
- Transition Probability
- Clustering
- Clustering Steps
- 1. Sampling
- 2. Parameter Selection
- 3. Transformation
- 4. Outliers
- 5. Data Scaling
- Distance Metric
- Clustering Techniques
- Minimum Spanning Tree-Clustering Method
- Minimum Spanning Tree Example
- Dendogram
- Nearest Centroid Method
- Cluster Interpretation
- Problems with Clustering
Presentation slides in Adobe Acrobat Format:
1 slide/page (641,232 bytes)
| 2 slides/page (322,220 bytes)
View presentation now:
Slides Only
| Slides+Audio: Part 1,
Part 2
| Slides+Video: Part 1,
Part 2
If you don't have a real media player, click here to view
Slides+Audio: Part 1,
Part 2
| Slides+Video: Part 1,
Part 2
Frequently asked questions about remote audio/video viewing
Right-click to download RealMedia files for local playback:
Slides+Audio Part 1 (2,454,369 bytes),
Part 2 (9,440,717 bytes)
| Slides + Video Part 1 (9,187,904 bytes),
Part 2 (11,237,411 bytes)
Instructions for local audio/video playback
Back to other lectures of the series
Complete List of Audio/Video Lectures by Raj Jain
Back to Raj Jain's Home Page