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Scheduling Large Jobs by Abstraction Refinement by Thomas A. Henzinger; Vasu Singh; Thomas Wies; Damien Zufferey is a scholarly article available to read on EtoBox.

What is Scheduling Large Jobs by Abstraction Refinement about?

The static scheduling problem often arises as a fundamental problem in real-time systems and grid computing. We consider the problem of statically scheduling a large job expressed as a task graph on a large number of computing nodes, such as a data center.This paper solves the large-scale static scheduling problem using abstraction refinement, a technique commonly used in formal verification to efficiently solve computationally hard problems. A scheduler based on abstraction refinement first attempts to solve the scheduling problem with abstract representations of the job and the computing resources. As abstract representations are generally small, the scheduling can be done reasonably fast. If the obtained schedule does not meet specified quality conditions (like data center utilization or schedule makespan) then the scheduler refines the job and data center abstractions and, again solves the scheduling problem. We develop different schedulers based on abstraction refinement. We implemented these schedulers and used them to schedule task graphs from various computing domains on simulated data centers with realistic topologies. We compared the speed of scheduling and the quality of

Author

Thomas A. Henzinger; Vasu Singh; Thomas Wies; Damien Zufferey

Publisher

ACM

Published

2011

Language

EN