Speculative Scheduling of Parameter Sweep Applications using Job Behaviour Descriptions

Related Work

Our approach focuses on the resource access of jobs; the scheduling decisions are made based on the finishing time estimations exploiting the knowledge of the behaviour of jobs.

Nabrizyski et al. (Nabrizyski, Schopf, & Weglarz, 2003) gives an excellent overview of Grid resource management. Besides presenting a number of scheduling strategies (Ranganathan & Foster, 2003), in Chapter 16 W. Smith introduces new statistical prediction techniques for the execution times for applications. The first technique uses historical information of previous similar runs to form predictions. The similarity of runs are determined by categorising discrete characteristics of the submitted jobs. The second technique uses instance-based learning: a database of experiences is maintained and used to make predictions. Each experience consists of input and output features. The input feature is a simple job description (user name, job name, number of CPUs requested, requested operating system, etc.).