Coauthors: E. Bampis, D. Letsios, and I. Nemparis

We are given a set of jobs, each one specified by its release date, its deadline and its processing volume (work), and a single (or a set of) speed-scalable processor(s). We adopt the standard model in speed-scaling in which if a processor runs at speed s then the energy consumption is s^α per time unit, where α>1. Our goal is to find a schedule respecting the release dates and the deadlines of the jobs so that the total energy consumption is minimized. We present our results from two recent papers concerning the preemptive and non-preemptive cases. For the multiprocessor preemptive speed-scaling problem, we give a transformation to the convex cost flow problem and we obtain a polynomial-time algorithm, simplifying the previous known algorithms for the problem. For the single-processor non-preemptive speed-scaling problem, we present an improved approximation algorithm. Finally, for the multiprocessor non-preemptive case, we propose improved approximation algorithms, for particular families of instances.