Paper Info
Title
Task-Allocation In A Large-Scaled Hierarchical Many-Core Topology
Abstract
As more and more electronic devices get connected together, whole systems get more complicated in terms of development, maintenance and usage. New principles in design are needed to cope with this complexity. That is why we developed the artificial hormone system (AHS). The AHS enables an autonomous and decentralized task-allocation among a set of processing elements (PEs). The AHS works good in small-scaled nonhierarchical scenarios. For larger scaled and hierarchical scenarios, we developed the hierarchical artificial hormone system (HAHS) and presented a first abstract concept of the recursive artificial hormone system (RAHS). Both utilize the AHS in isolated smaller clusters of PEs to achieve the same functionality as the AHS with less communication. Thus, the whole task-set will be split into smaller and disjoint task-subsets which then will be distributed to the clusters. The HAHS uses a two-level hierarchy with a second regulation cycle between all clusters. The RAHS on the other hand is designed to manage a n-level hierarchy. In this article, we will present the first two implemented versions of the RAHS, their evaluation, and the comparison to the original AHS.
Year
DOI
Venue
2021
10.1002/cpe.5731
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
Keywords
DocType
Volume
artificial hormone system, decentralized, organic computing, reliability, self-x, task-allocation
Journal
33
Issue
ISSN
Citations 
14
1532-0626
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Andreas Lund121.09
Uwe Brinkschulte241252.57