Self-Organisation and Evolution for Trust-Adaptive Grid Computing Agents

  • Yvonne Bernard
  • Lukas Klejnowski
  • David Bluhm
  • Jörg Hähner
  • Christian Müller-Schloer


The Organic Computing (OC) initiative aims at introducing new, self-organising algorithms in order to cope better with the complexity of today’s systems. One approach to self-organisation is the introduction of agents which are able to continuously adapt their behaviour to changing environmental conditions and thus collectively create an efficient and robust system. In this paper, we introduce an evolutionary approach to an agent which acts autonomously and optimises its behaviour at run-time. The behaviour of the Evolutionary Agent is defined by ten chromosomes. When two agents interact, the inferior agent copies a part of the genes of the more successful agent. Therefore, the most successful gene combination will spread throughout the network. Application scenario for our evaluation is the Trusted Desktop Grid, a distributed system where computing resources are shared by autonomously acting agents.


High Fitness Evolutionary Agent Successful Agent Chromosome Structure Work Unit 
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.



This research is funded by the research unit “OC-Trust” (FOR 1085) of the German Research Foundation (DFG).


  1. 1.
    Müller-Schloer, C., Schmeck, H.: Organic computing - Quo Vadis? In: Müller-Schloer, C., Schmeck, H., Ungerer, T. (eds.) Organic Computing - A Paradigm Shift for Complex Systems, chapter  6.2. Birkhäuser, Basel (2011)Google Scholar
  2. 2.
    Bernard, Y., Klejnowski, L., Hähner, J., Müller-Schloer, C.: Efficiency and robustness using trusted communities in a trusted desktop grid. In: Proceedings of the 2011 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshop (SASOW). IEEE Computer Society Press (2011)Google Scholar
  3. 3.
    Choi, S., Kim, H., Byun, E., Baik, M., Kim, S., Park, C., Hwang, C.: Characterizing and classifying desktop grid. In: 7th IEEE International Symposium on Cluster Computing and the Grid, 2007, pp. 743–748. CCGRID 2007 (2007)Google Scholar
  4. 4.
    Anderson, D.P.: Public computing: reconnecting people to science. In: Conference on Shared Knowledge and the Web. Residencia de Estudiantes, Madrid (2003)Google Scholar
  5. 5.
    Amoretti, M.: A framework for evolutionary peer-to-peer overlay schemes. In: Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing, EvoWorkshops 2009, pp. 61–70. Springer (2009)Google Scholar
  6. 6.
    Tyson, G., Grace, P., Mauthe, A., Kaune, S.: The survival of the fittest: an evolutionary approach to deploying adaptive functionality in peer-to-peer systems. In: Proceedings of the 7th Workshop on Reflective and Adaptive Middleware, ARM ’08, pp. 23–28. ACM, New York (2008)Google Scholar
  7. 7.
    Mui, L., Mohtashemi, M., Halberstadt, A.: A computational model of trust and reputation. In: Proceedings of the 35th Annual Hawaii International Conference on HICSS System Sciences, pp. 2431–2439, 7–10 Jan 2002Google Scholar
  8. 8.
    Zhao H, Li, X.: H-trust: a robust and lightweight group reputation system for peer-to-peer desktop grid. In: 28th International Conference on Distributed Computing Systems Workshops. ICDCS ’08, pp. 235–240, June 2008Google Scholar
  9. 9.
    Chakravarti, A.J., Baumgartner, G., Lauria, M.: The organic grid: self-organizing computation on a peer-to-peer network. IEEE T. Syst. Man Cy. A: Syst. Hum. 35(3), 373–384 (2005)CrossRefGoogle Scholar
  10. 10.
    Macy, M.W., Skvoretz, J.: The evolution of trust and cooperation between strangers: a computational model. Technical Report, October (1998)Google Scholar
  11. 11.
    Cakar, E.: Population-based runtime optimisation in static and dynamic environments. Ph.D. thesis, Leibniz Universität Hannover (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Yvonne Bernard
    • 1
  • Lukas Klejnowski
    • 1
  • David Bluhm
    • 1
  • Jörg Hähner
    • 1
  • Christian Müller-Schloer
    • 1
  1. 1.Institut für Systems EngineeringFG System- und Rechnerarchitektur Leibniz Universität HannoverHannoverGermany

Personalised recommendations