Abstract
As mobile devices become more powerful, interprocess communication becomes increasingly more important. Unfortunately, this larger freedom of mobility gives rise to unknown environments. In these environments, processes that want to communicate with each other will be unable to do so because of protocol conflicts. Although conflicting protocols can be remedied by using adaptors, the number of possible combinations of different protocols increases dramatically. Therefore we propose a technique to generate protocol adaptors automatically. This is realised by means of genetically engineered classifier systems that use Petri nets as a specification for the underlying protocols. This paper reports on an experiment that validates this approach.
Corresponding author. He is developing peer-to-peer embedded systems for a project funded by the Flemish Institute for Science and Technology (IWT).
Tom Mens is a Postdoctoral Fellow of the Fund for Scientific Research—Flanders (Belgium)
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hoare, C.: Communicating Sequential Processes. International Series in Computer Science. Prentice Hall (1985)
Milner, R.: Communicating and Mobile Systems: the π-calculus. Cambridge University Press (1999)
Lea, D.: Concurrent Programming in Java (2nd edition) Design Principles and Patterns. The Java Series. Addison Wesley (2000)
Reisig, W.: An Informal Introduction To Petri Nets. Proc. Int’l Conf. Application and Theory of Petri Nets, Aarhus, Denmark (2000)
Glodberg, D. E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley (1989)
Kröse, B., van der Smagt, P.: An introduction to neural networks. University of Amsterdam (1996)
Sutton, R. S., Barto, A. G.: Reinforcement Learning—An Introduction. MIT Press (1998)
Smith, S.: A Learning System Based on Genetic Adaptive Algorithms. PhD thesis, Department of Computer Science, University of Pittsburgh (1980)
Bull, L., Fogarty, T.: Co-evolving communicating classifier systems for tracking. Proc. Int’l Conf. Neural Networks and Genetic Algoriths (1993)
Koza, J. R.: Genetic Programming; on the programming of computers by means of natural selection. MIT Press (1992)
Morgenstern, L.: The problem with solutions to the frame problem. In Ford, K. M., Pylyshyn, Z., eds.: The Robot’s Dilemma Revisited: The Frame Problem in Artificial Intelligence. Ablex Publishing Co., Norwood, New Jersey (1996) 99–133
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Van Belle, W., Mens, T., D’Hondt, T. (2003). Using Genetic Programming to Generate Protocol Adaptors for Interprocess Communication. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds) Evolvable Systems: From Biology to Hardware. ICES 2003. Lecture Notes in Computer Science, vol 2606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36553-2_38
Download citation
DOI: https://doi.org/10.1007/3-540-36553-2_38
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00730-2
Online ISBN: 978-3-540-36553-2
eBook Packages: Springer Book Archive