By Topic

Empirical evaluation of weighted and prioritized static scheduling heuristics for real-time multiprocessing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ronngren, S. ; Dept. of Comput. Sci. Eng., Texas Univ., Arlington, TX, USA ; Shirazi, B. ; Lorts, D.

Suboptimal solutions to the NP-complete problem of task scheduling in a multiprocessing system are achievable with the aid of heuristic methods. Static scheduling heuristics for real-time multiprocessing systems are typically based on existing algorithms developed for non-real-time systems. Unfortunately this approach results in the real-rime heuristics inheriting the deficiencies of the non-real-time algorithms as well. Existing scheduling heuristics compromise the results of the scheduling effort by insufficiently representing the task characteristics of an application graph. In this paper we present results of experimentation in which the parameters of the DAG are enhanced to more accurately correspond to those of real-world real-time applications. A method of specifying weighted combinations and priorities of simple scheduling heuristics as the scheduling algorithm is presented. Results of the compound heuristics are compared to the results of previous work in the field with some interesting conclusions

Published in:

Parallel and Distributed Real-Time Systems, 1994. Proceedings of the Second Workshop on

Date of Conference:

28-29 Apr 1994