UC Santa Cruz

Prediction is a powerful tool for performance and usability. It can reduce access latency for I/O systems, and can improve usability for mobile computing systems by automating the file hoarding process. We present recent research that has resulted in a file successor predictor that matches the performance of state-of-the-art context-modeling predictors, while requiring a small fraction of their space requirements. Noah is an on-line algorithm for predicting successor file access events, effectively identifying strong pairings (successor relationships) among files. Noah can accurately predict approximately 80% of all file access events, while tracking only two candidate successors of which only one requires regular dynamic updates.