By Topic

An Agressive Strategy for an Artificial Hormone System to Minimize the Task Allocation Time

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)
Brinkschulte, U. ; Inst. fur Inf., Johann Wolfgang Goethe Univ., Frankfurt, Germany ; Pacher, M.

We present an aggressive task allocation strategy for an Artificial Hormone System (AHS). The AHS is a completely decentralized operation principle for a middleware which can be used to allocate tasks in a system of heterogeneous processing elements (PEs) or cores. Tasks are scheduled according to suitability of the heterogeneous PEs, current PE load and task relationships. In addition, the AHS provides properties like self-configuration, self-optimization and self-healing by task allocation. The AHS is able to guarantee real-time bounds regarding these self-X-properties. The aggressive task allocation strategy presented in this paper allows to halve the worst case execution times for the self-X-properties compared to previous strategies thus improving the suitability of the AHS for hard real-time systems.

Published in:

Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW), 2012 15th IEEE International Symposium on

Date of Conference:

11-11 April 2012