This IST research group developed a prototype scheduling system called Flextic, which can take these differences into account. Key to Flextic's approach is a set of desired operational characteristics submitted by the user, such as how much data will be processed and the maximum amount of time the job should take to execute. "We want to be able to ask some information about a job we are doing," Zufferey said.

Scheduling can be affected by other factors as well. For instance, when you move a virtual machine from one server to another while it is still running, it can slow down all the other virtual machines running on each of those servers, said Seung-Hwan Lim, a Pennsylvania State University researcher who co-authored a paper on this topic with Chita R. Das, of Pennsylvania State University, and Jae-Seok Huh and Youngjae Kim of Oak Ridge National Laboratory.

These researchers looked at ways of quantifying the overall effect that moving a virtual machine would have on its surrounding workloads. "In order to have robust and predictable performance, we need migration-aware schedulers," Lim said.

The IDG News Service