To Do or Not To Do: Scheduling to Minimize Energy


August 18, 2015


Samir Khuller


University of Maryland


Traditional scheduling algorithms, especially those involving job scheduling on parallel machines, make the assumption that the machines are always available and try to schedule jobs to minimize specific job related metrics. Since modern data centers consume massive amounts of energy, we consider job scheduling problems that take energy consumption into account, turning machines off, especially during periods of low demand. The ensuing problems relate very closely to classical covering problems such as capacitated set cover, and we discuss several recent results in this regard.

(This is talk covers two papers, and is joint work with Jessica Chang, Hal Gabow and Koyel Mukherjee.)


Samir Khuller

Samir Khuller is a Professor and the Elizabeth Iribe Chair in the Department of Computer Science. His research interests are in graph algorithms, discrete optimization, and computational geometry. He received the University of Maryland’s Distinguished Scholar Teacher Award 2007, as well as a Google Research Award. He received his M.S. and Ph.D. from Cornell University and his undergraduate degree from IIT-Kanpur. He spent two years as a research associate in UMIACS, before joining the Department of Computer Science.