Affiliation:
1. IBM T.J. Watson Research, Yorktown, NY
2. Google Inc., Mountain View, CA
Abstract
We consider the problem of minimizing the total weighted flow time on a single machine with preemptions. We give an online algorithm that is
O
(
k
)-competitive for
k
weight classes. This implies an
O
(log
W
)-competitive algorithm, where
W
is the maximum to minimum ratio of weights. This algorithm also implies an
O
(log
n
+ log
P
)-approximation ratio for the problem, where
P
is the ratio of the maximum to minimum job size and
n
is the number of jobs. We also consider the nonclairvoyant setting where the size of a job is unknown upon its arrival and becomes known to the scheduler only when the job meets its service requirement. We consider the resource augmentation model, and give a (1 + ε)-speed, (1 +1/ε)-competitive online algorithm.
Publisher
Association for Computing Machinery (ACM)
Subject
Mathematics (miscellaneous)
Cited by
27 articles.
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