Caching in the Sprite network file system
ACM Transactions on Computer Systems (TOCS)
Disconnected operation in the Coda File System
ACM Transactions on Computer Systems (TOCS)
Cache management algorithms for flexible filesystems
ACM SIGMETRICS Performance Evaluation Review
Design and Implementation of a Predictive File Prefetching Algorithm
Proceedings of the General Track: 2002 USENIX Annual Technical Conference
Using Multiple Predictors to Improve the Accuracy of File Access Predictions
MSS '03 Proceedings of the 20 th IEEE/11 th NASA Goddard Conference on Mass Storage Systems and Technologies (MSS'03)
Performing File Prediction with a Program-Based Successor Model
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Towards Building a Fault Tolerant and Conflict-Free Distributed File System for Mobile Clients
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 02
File access prediction with adjustable accuracy
PCC '02 Proceedings of the Performance, Computing, and Communications Conference, 2002. on 21st IEEE International
An analytical approach to file prefetching
ATEC '97 Proceedings of the annual conference on USENIX Annual Technical Conference
Why does file system prefetching work?
ATEC '99 Proceedings of the annual conference on USENIX Annual Technical Conference
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File prediction is the process of bringing necessary files into cache before they are needed, while file caching is the process of maintaining required data in memory for future reuse. Our combined concept, which is the cache-based file prediction, is designed to support the main objectives of the Paradise File System, which are to provide high available and reliable storage for files, and guarantees that file operations are executed in spite of concurrency and failures. In this paper, we show that our cache-based file prediction scheme is efficient and practical by describing its design and implementation. Moreover, we report on its performance evaluation using a cluster of workstations. Our results indicate clearly that our design exhibits a significant degree of files availability and prediction accuracy