Approximation Algorithms for Resource
Cost Aware Scheduling
Rodrigo Carrasco
Abstract
Managing non-renewable resource consumption is fast emerging as a problem of critical importance.
There is always a trade-off between resource consumption and performance: more resource
consumption typically results in better performance. We are interested in the scheduling problem
where there are several different resources that determine the speed at which a job runs, such as CPU
speed, RAM size, bus speed/size, etc., and we pay depending on the amount of resources that we use.
This work is an extension of the resource dependent job processing time problem and the energy
aware scheduling problem.
We develop a new constant factor approximation algorithm for resource cost aware scheduling
problems: the objective is to minimize the sum of the total cost of resources and the total weighted
completion time in the one machine non-preemptive setting, allowing for arbitrary precedence
constraints and release dates. Our algorithm handles general job-dependent resource cost functions.
We also analyze the practical performance of our algorithms, showing that it is significantly superior
to the theoretical bounds and in fact are very close to optimal. We also present additional
improvements and we study their performance in other settings.
1