Paper Info
Title
An Agressive Strategy for an Artificial Hormone System to Minimize the Task Allocation Time
Abstract
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.
Year
DOI
Venue
2012
10.1109/ISORCW.2012.40
Object/Component/Service-Oriented Real-Time Distributed Computing Workshops
Keywords
Field
DocType
task relationship,task allocation time,current pe load,aggressive task allocation strategy,artificial hormone system,task allocation,agressive strategy,heterogeneous pes,heterogeneous processing element,real-time bound,hard real-time system,previous strategy,resource management,embedded system,biochemistry,self organization,silicon,task analysis,real time systems,worst case execution time,real time,embedded systems,middleware,resource manager
Resource management,Middleware,Task analysis,Computer science,Self-organization,Real-time computing,Embedded system,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-4673-0900-4
11
0.69
References 
Authors
9
2
Name
Order
Citations
PageRank
Uwe Brinkschulte141252.57
Mathias Pacher210713.21