Abstract
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.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-642-37577-4_18
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
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)
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)
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)
Anderson, D.P.: Public computing: reconnecting people to science. In: Conference on Shared Knowledge and the Web. Residencia de Estudiantes, Madrid (2003)
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)
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)
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 2002
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 2008
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)
Macy, M.W., Skvoretz, J.: The evolution of trust and cooperation between strangers: a computational model. Technical Report, October (1998)
Cakar, E.: Population-based runtime optimisation in static and dynamic environments. Ph.D. thesis, Leibniz Universität Hannover (2011)
Acknowledgements
This research is funded by the research unit “OC-Trust” (FOR 1085) of the German Research Foundation (DFG).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bernard, Y., Klejnowski, L., Bluhm, D., Hähner, J., Müller-Schloer, C. (2014). Self-Organisation and Evolution for Trust-Adaptive Grid Computing Agents. In: Cagnoni, S., Mirolli, M., Villani, M. (eds) Evolution, Complexity and Artificial Life. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37577-4_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-37577-4_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37576-7
Online ISBN: 978-3-642-37577-4
eBook Packages: Computer ScienceComputer Science (R0)