**Talk:** Algorithmic problems in power management of computing systems

**Speaker:** Georgios Zois

### Abstract:

This work is focused on energy-efficient algorithms for job scheduling
problems on speed-scalable processors, as well as on processors operating
under a thermal and cooling mechanism, where, for a given budget of energy
or a thermal threshold, the goal is to optimize a Quality of Service
criterion. A part of our research concerns scheduling problems arising in
large-data processing environments. In this context, we focus on the
MapReduce paradigm and we consider problems of energy-efficient scheduling
on multiple speed-scalable processors as well as classical scheduling on a
set of unrelated processors.
First, we propose complexity results, optimal and constant competitive
algorithms for different energy-aware variants of the problem of
minimizing the maximum lateness of a set of jobs on a single
speed-scalable processor. Then, we consider energy-aware MapReduce
scheduling as well as classical MapReduce scheduling (where energy is not
our concern) on unrelated processors, where the goal is to minimize the
total weighted completion time of a set of MapReduce jobs. We study
special cases and generalizations of both problems and propose constant
approximation algorithms. Finally, we study temperature-aware scheduling
on a single processor that operates under a strict thermal threshold,
where each job has its own heat contribution and the goal is to maximize
the schedule's throughput. We consider the case of unit-length jobs with a
common deadline and we study the approximability of the problem.