Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Self-Organized Task Allocation for Service Tasks in Computing Systems with Reconfigurable Components

  • Published:
Journal of Mathematical Modelling and Algorithms

Abstract

A self-organized scheme for the allocation service tasks in adaptive or organic computing systems is proposed. Such computing systems are highly self-organized and the components ideally adapt to the needs of users or the environment. Typically, the components of such systems need some service from time to time in order perform their work efficiently. Since the type of service tasks will often change in this systems it is attractive to use reconfigurable hardware to perform the service tasks. The studied system consists of normal worker components and the helper components which have reconfigurable hardware and can perform different service tasks. The speed with which a service task is executed by a helper depends on its actual configuration. Different strategies for the helpers to decide about service task acceptance and reconfiguration are proposed. These task acceptance strategies are inspired by stimulus-threshold models that are used to explain task allocation in social insects. Analytical results for a system with two reconfigurable helpers are presented together with simulation results for larger systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Agassounon, W., Martinoli, A.: Efficiency and robustness of threshold-based distributed allocation algorithms in multi-agent systems. In: Proc. of the First Int. Joint Conf. on Autonomous Agents and Multi-Agent Systems AAMAS-02, pp. 1090–1097. ACM Press (2002)

  2. Bonabeau, E., Theraulaz, G., Deneubourg, J.-L.: Fixed response thresholds and the regulation of division of labor in insect societies. Bull. Math. Biol. 60, 753–807 (1998)

    Article  MATH  Google Scholar 

  3. Bonabeau, E., Sobkowski, A., Theraulaz, G., Deneubourg, J.-L.: Adaptive task allocation inspired by a model of division of labor in social insects. In: Lundh, D. et al. (eds.) Biocomputing and Emergent Computation, pp. 36–45. World Scientific (1997)

  4. Bonabeau, E., Theraulaz, G., Deneubourg, J.-L.: Quantitative study of the fixed threshold model for the regulation of division of labour in insect societies. Proc. Roy. Soc. London B 263, 1565–1569 (1996)

    Article  Google Scholar 

  5. Cicirello, V.A., Smith, S.F.: Wasp-like agents for distributed factory coordination. Auton. Agentsand Multi-Agent Syst. 8(3), 237–266 (2004)

    Article  Google Scholar 

  6. Cicirello, V.A., Smith, S.F.: Distributed coordination of resources via wasp-like agents. Proc. First NASA GSFC/JPL Workshop on Radical Agent Concepts (WRAC), pp. 71–80 (2003)

  7. Cicirello, V.A., Smith, S.F.: Wasp nests for self-configurable factories. Proc. Fifth Int. Conf. on Autonomous Agents, pp. 473–480 (2001)

  8. Cicirello, V.A., Smith, S.F.: Insect Societies and Manufacturing IJCAI-01 Workshop on Artificial Intelligence and Manufacturing (2001)

  9. Ferreira, P.R., de Oliveira, D., Bazzan, A.L.C.: A swarmbased approach to adapt the structural dimension of agents’ organization. J. Braz. Comput. Soc. 11(1), 63–73 (2005)

    Google Scholar 

  10. Gautrais, J., Theraulaz, G., Deneubourg, J.-L., Anderson, C.: Emergent polyethism as a consequence of increased colony size in insect societies. J. Theor. Biol. 215, 363–373 (2002)

    Article  Google Scholar 

  11. GI: Organic Computing / VDE, ITG, GI—Positionspapier. 2003, online: http://www.betriebssysteme.org/Betriebssysteme/FutureTrends/oc-positionspapier.pdf

  12. Kephart, J.O., Chess, D.M.: The vision of autonomic computing. IEEE Comput. 36(1), 41–50 (2003)

    Google Scholar 

  13. Kittithreerapronchai, O., Anderson, C.: Do ants paint trucks better than chickens? Market versus response thresholds for distributed dynamic scheduling. Proc. IEEE Congress on Evolutionary Computation (2003)

  14. Krieger, M.J.B., Billeter, J.-B.: The call of duty: selforganised task allocation in a population of up to twelve mobile robots. Robot. Autonom. Sys. 30, 65–84 (2000)

    Article  Google Scholar 

  15. Merkle, D., Middendorf, M.: Dynamic polyethism and competition for tasks in threshold reinforcement models of social insects. Adapt. Behav. 12, 251–262 (2004)

    Article  Google Scholar 

  16. Müller-Schloer, C., von der Malsburg, C., Würtz, R.P.: Organic computing. Informatik Spektrum 27(4), 332–336 (2004)

    Article  Google Scholar 

  17. Schmeck, H.: Organic computing—a new vision for distributed embedded systems. Proc. of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC 2005), pp. 201–203 (2005)

  18. Price, R., Tino, P.: Evaluation of adaptive nature inspired task allocation against alternate decentralised multiagent strategies. Proc. Parallel Problem Solving from Nature—PPSN VIII, pp. 982–990. LNCS 3242, Springer (2004)

  19. Theraulaz, G., Bonabeau, E., Deneubourg, J.: Response threshold reinforcement and division of labour in insect societies. Proc. Roy. Soc. London B 265, 327–332 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander Scheidler.

Additional information

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.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Merkle, D., Middendorf, M. & Scheidler, A. Self-Organized Task Allocation for Service Tasks in Computing Systems with Reconfigurable Components. J Math Model Algor 7, 237–254 (2008). https://doi.org/10.1007/s10852-008-9079-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10852-008-9079-8

Keywords

Navigation