Using program and user information to improve file prediction performance
Tsozen Yeh, Darrell D. E. Long, Scott Brandt · 2005
Correct prediction of file accesses can improve system performance by mitigating the relative speed difference between CPU and disks. This paper discusses Program-based Last Successor (PLS) and presents Program- and Userbased Last Successor (PULS), file prediction algorithms that utilize information about the program and user that access the files. Our simulation results show that PLS makes 21% fewer incorrect predictions and PULS makes 24% fewer incorrect predictions than last-successor with roughly the same number of correct predictions that lastsuccessor makes. The cache space wasted on incorrect predictions can be reduced accordingly. We also show that a cache using the Least Recently Used (LRU) caching algorithm can perform better when the PULS is applied. In some cases, a cache using LRU and either PLS or PULS performs better than a cache up to 40 times larger using LRU alone.