Nonclairvoyant Speed Scaling for Flow and Energy

  • Authors:
  • Ho-Leung Chan;Jeff Edmonds;Tak-Wah Lam;Lap-Kei Lee;Alberto Marchetti-Spaccamela;Kirk Pruhs

  • Affiliations:
  • The University of Hong Kong, Hong Kong, Hong Kong;York University, Toronto, Ontario, Canada;The University of Hong Kong, Hong Kong, Hong Kong;Max-Planck-Institut für Informatik, 66123, Saarbrücken, Germany;Sapienza Università di Roma, Dipartimento di Informatica e Sistemistica, 00185, Roma, Italy;University of Pittsburgh, 15260, Pittsburgh, PA, USA

  • Venue:
  • Algorithmica
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

We give three results related to online nonclairvoyant speed scaling to minimize total flow time plus energy. We give a nonclairvoyant algorithm LAPS, and show that for every power function of the form P(s)=s α , LAPS is O(1)-competitive; more precisely, the competitive ratio is 8 for α=2, 13 for α=3, and $\frac{2\alpha^{2}}{\ln\alpha}$ for α3. We then show that there is no constant c, and no deterministic nonclairvoyant algorithm A, such that A is c-competitive for every power function of the form P(s)=s α . So necessarily the achievable competitive ratio increases as the steepness of the power function increases. Finally we show that there is a fixed, very steep, power function for which no nonclairvoyant algorithm can be O(1)-competitive.