By Topic

An augmented approach to task allocation: combining simulated annealing with list-based heuristics

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

2 Author(s)
Wells, B.E. ; Dept. of Electr. & Comput. Eng., Alabama Univ., Huntsville, AL, USA ; Carroll, C.C.

Static task allocation is concerned with the assignment, scheduling, and mapping of individual units of execution among a set of parallel processors in a manner that results in near-optimal performance. Two types of heuristics often applied individually to the allocation problem are list-based methodologies and simulated annealing. This paper describes the results of combining these two approaches to create an improved heuristic that produces quality allocations for certain types of real-time and deterministic systems. The resulting methodology performs static allocations of non-preemptive executable tasks to the available set of processors that are interconnected to one another via an arbitrarily-linked static message-passing topology. Its effectiveness is analyzed empirically by applying it to randomly-generated task systems that span a wide range of inherent concurrency, and by applying it to the task system of a simulation of a Space Shuttle main rocket engine

Published in:

Parallel and Distributed Processing, 1993. Proceedings. Euromicro Workshop on

Date of Conference:

27-29 Jan 1993