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Summary: Maximizing Job Bene ts On-line
Baruch Awerbuch y Yossi Azar z Oded Regev x
November 19, 2000
Abstract
We consider a bene t model for on-line preemptive scheduling. In this
model jobs arrive at the on-line scheduler at their release time. Each job
arrives with its own execution time and bene t function. The
ow time
of a job is the time that passes from its release to its completion. The
bene t function speci es the bene t gained for any given
ow time. A
scheduler's goal is to maximize the total bene t gained. We present a
constant competitive ratio algorithm for that model in the uniprocessor
case for bene t functions that do not decrease too rapidly. We also extend
the algorithm to the multiprocessor case while maintaining constant com-
petitiveness. The multiprocessor algorithm does not use migration, i.e.,
preempted jobs continue their execution on the same processor on which
they were originally processed.
1 Introduction
1.1 The basic problem
We are given a sequence of n jobs to be assigned to one machine. Each job j
has a release time r j and a length or execution time w j . Each job is known
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