Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
In systems consisting of multiple clusters of processors which are interconnected by relatively slow communication links and which employ space sharing for scheduling jobs, such a...
We study the online version of the classical parallel machine scheduling problem to minimize the total weighted completion time from a new perspective: We assume that the data of ...
This paper proposes a new scheduling policy for cluster-based servers called DAS (Deferred Assignment Scheduling). The main idea in DAS is to defer scheduling as much as possible,...
Victoria Ungureanu, Benjamin Melamed, Michael N. K...
Large-scale computing environments, such as TeraGrid, Distributed ASCI Supercomputer (DAS), and Grid’5000, have been using resource co-allocation to execute applications on mult...