Dynamic scheduling of parallel real-time jobs by modelling spare capabilities in heterogeneous clusters

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

Colleges, School and Institutes

External organisations

  • University of Warwick

Abstract

In this research, a scenario is assumed where periodic real-time jobs are being run on a heterogeneous cluster of computers, and new aperiodic parallel real-time jobs, modelled by Directed Acyclic Graphs (DAG), arrive at the system dynamically. In the scheduling scheme presented in this paper, a global scheduler situated within the cluster schedules new jobs onto the computers by modelling their spare capabilities left by existing periodic jobs. Admission control is introduced so that new jobs are rejected if their deadlines cannot be met under the precondition of still guaranteeing the real-time requirements of existing jobs. Each computer within the cluster houses a local scheduler, which uniformly schedules both periodic job instances and the subtasks in the parallel realtime jobs using an Early Deadline First policy. The modelling of the spare capabilities is optimal in the sense that once a new task starts running on a computer, it will utilize all the spare capability left by the periodic real-time jobs and its finish time is the earliest possible. The performance of the proposed modelling approach and scheduling scheme is evaluated by extensive simulation; results show that the system utilization is significantly enhanced, while the real-time requirements of the existing jobs remain guaranteed.

Bibliographic note

Publisher Copyright: © 2003 IEEE.

Details

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Cluster Computing, CLUSTER 2003
Publication statusPublished - 2003
EventIEEE International Conference on Cluster Computing, CLUSTER 2003 - Hong Kong, China
Duration: 1 Dec 20034 Dec 2003

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
Volume2003-January
ISSN (Print)1552-5244

Conference

ConferenceIEEE International Conference on Cluster Computing, CLUSTER 2003
Country/TerritoryChina
CityHong Kong
Period1/12/034/12/03