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Theory in Biosciences

, Volume 127, Issue 2, pp 149–161 | Cite as

Stability and performance of ant queue inspired task partitioning methods

  • Alexander Scheidler
  • Daniel Merkle
  • Martin Middendorf
Original Paper

Abstract

In this paper, we consider computing systems that have autonomous helper components which fulfill support functions and that possess reconfigurable hardware so that they can specialize to different types of service tasks. Several self-organized task partitioning methods are proposed that can be used by the helper components to decide how to reconfigure and which service tasks to execute. The proposed task partitioning methods are inspired by the so-called ant queue system that can be found in real ants for partitioning tasks between the individuals. The aim of this study is to investigate basic properties of the task partitioning methods, like stability and efficiency, in order to obtain basic insights into the design of task partitioning methods in self-organized service systems. More precisely, the investigations are threefold: (1) discrete event simulations are used to investigate systems, (2) for a simple version of the task partitioning system analytical stability results are obtained by means of delay differential equation systems and (3) by numerically solving initial value problems.

Keywords

Execution Time Social Insect Delay Differential Equation Reconfigurable Hardware Task Partitioning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by the German Research Foundation (DFG) through the project “Organisation and control of self-organising systems in technical compounds” within SPP 1183.

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Alexander Scheidler
    • 1
  • Daniel Merkle
    • 2
  • Martin Middendorf
    • 1
  1. 1.Department of Computer ScienceUniversity of LeipzigLeipzigGermany
  2. 2.Departement of Mathematics and Computer ScienceUniversity of Southern DenmarkOdense MDenmark

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