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ACTA
2010
91views more  ACTA 2010»
13 years 6 months ago
A theoretical comparison of LRU and LRU-K
The paging algorithm Least Recently Used Second Last Request (LRU-2) was proposed for use in database disk buffering and shown experimentally to perform better than Least Recently ...
Joan Boyar, Martin R. Ehmsen, Jens S. Kohrt, Kim S...
CORR
2010
Springer
83views Education» more  CORR 2010»
13 years 9 months ago
List Factoring and Relative Worst Order Analysis
Relative worst order analysis is a supplement or alternative to competitive analysis which has been shown to give results more in accordance with observed behavior of online algori...
Martin R. Ehmsen, Jens S. Kohrt, Kim S. Larsen
JCSS
2007
89views more  JCSS 2007»
13 years 11 months ago
The relative worst-order ratio applied to paging
The relative worst order ratio, a new measure for the quality of on-line algorithms, was recently defined and applied to two bin packing problems. Here, we extend the definition ...
Joan Boyar, Lene M. Favrholdt, Kim S. Larsen
JCO
2006
83views more  JCO 2006»
13 years 11 months ago
Separating online scheduling algorithms with the relative worst order ratio
The relative worst order ratio is a measure for the quality of online algorithms. Unlike the competitive ratio, it compares algorithms directly without involving an optimal offline...
Leah Epstein, Lene M. Favrholdt, Jens S. Kohrt
SWAT
2004
Springer
136views Algorithms» more  SWAT 2004»
14 years 4 months ago
The Relative Worst Order Ratio Applied to Seat Reservation
The seat reservation problem is the problem of assigning passengers to seats on a train with n seats and k stations enroute in an online manner. The performance of algorithms for t...
Joan Boyar, Paul Medvedev
WADS
2009
Springer
298views Algorithms» more  WADS 2009»
14 years 6 months ago
A Comparison of Performance Measures for Online Algorithms
This paper provides a systematic study of several proposed measures for online algorithms in the context of a specific problem, namely, the two server problem on three colinear po...
Joan Boyar, Sandy Irani, Kim S. Larsen