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Minimizing stall time in single and parallel disk systems

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44477

Garg,  Naveen
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons43989

Albers,  Susanne
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44913

Leonardi,  Stefano
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Volltexte (frei zugänglich)

1997-1-024
(beliebiger Volltext), 10KB

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Zitation

Garg, N., Albers, S., & Leonardi, S.(1997). Minimizing stall time in single and parallel disk systems (MPI-I-1997-1-024). Saarbrücken: Max-Planck-Institut für Informatik.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-9D69-1
Zusammenfassung
We study integrated prefetching and caching problems following the work of Cao et al. and Kimbrel and Karlin. Cao et al. and Kimbrel and Karlin gave approximation algorithms for minimizing the total elapsed time in single and parallel disk settings. The total elapsed time is the sum of the processor stall times and the length of the request sequence to be served. We show that an optimum prefetching/caching schedule for a single disk problem can be computed in polynomial time, thereby settling an open question by Kimbrel and Karlin. For the parallel disk problem we give an approximation algorithm for minimizing stall time. Stall time is a more realistic and harder to approximate measure for this problem. All of our algorithms are based on a new approach which involves formulating the prefetching/caching problems as integer programs.