Dynamic speed scaling to manage energy and temperature

We first consider online speed scaling algorithms to minimize the energy used subject to the constraint that every job finishes by its deadline. We assume that the power required to run at speed s is P(s) = s(alpha). We provide a tight alpha(alpha) bound on the competitive ratio of the previously proposed Optimal Available algorithm. This improves the best known competitive ratio by a factor of 2(alpha). We then introduce a new online algorithm, and show that this algorithm's competitive ratio is at most 2(alpha/(alpha-1))(alpha)e(alpha). This competitive ratio is significantly better and is approximately 2e(alpha+1) for large alpha. Our result is essentially tight for large alpha. In particular as alpha approaches infinity, we show that any algorithm must have competitive ratio e(alpha) (up to lower order terms). We then turn to the problem of dynamic speed scaling to minimize the maximum temperature that the device ever reaches, again subject to the constraint that all jobs finish by their deadlines. We assume that the device cools according to Fourier's law. We show how to solve this problem in polynomial time, within any error bound, using the Ellipsoid algorithm.