Energy Efficient Scheduling via Partial Shutdown

Abstract

We define a collection of new problems referred to as ``machine activation''
problems. The  central framework we introduce considers a collection of M
machines (unrelated  or related), with machine $i$ having an activation
cost of $a_i$.
There is also a collection of N jobs that need to be performed, and
$p_{ij}$ is the processing time of job $j$ on machine $i$.
Standard scheduling models assume that the set of machines is fixed
and all machines are available. We assume that there is an activation cost
budget of $A$
-- we would like to select a subset S of the machines to activate
with total cost $a(S)le A$ and find a schedule for the jobs on the
machines in $S$ minimizing the makespan. In this work we develop
bi-criteria approximation algorithms for this problem based on both
LP rounding and a greedy approach.