Abstract
This paper studies a bio-inspired framework, iNet-EGT, to build autonomous adaptive network applications. In iNet-EGT, each application is designed as a set of agents, each of which provides a functional service and possesses biological behaviors such as migration, replication and death. iNet-EGT implements an adaptive behavior selection mechanism for agents. It is designed after an immune process that produces specific antibodies to antigens (e.g., viruses) for eliminating them. iNet-EGT models a set of network conditions (e.g., workload and resource availability) as an antigen and an agent behavior as an antibody. iNet-EGT allows each agent to autonomously sense its surrounding network conditions (an antigen) and select a behavior (an antibody) according to the conditions. This behavior selection process is modeled as a series of evolutionary games among behaviors. It is theoretically proved to converge to an evolutionarily stable (ES) equilibrium; a specific (i.e., ES) behavior is always selected as the most rational behavior against a particular set of network conditions. This means that iNet-EGT allows every agent to always perform behaviors in a rational and adaptive manner. Simulation results verify this; agents invoke rational (i.e., ES) behaviors and adapt their performance to dynamic network conditions.
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Lee, C., Suzuki, J., Vasilakos, A.V. (2010). iNet-EGT: An Evolutionarily Stable Adaptation Framework for Network Applications. In: Altman, E., Carrera, I., El-Azouzi, R., Hart, E., Hayel, Y. (eds) Bioinspired Models of Network, Information, and Computing Systems. BIONETICS 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12808-0_4
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DOI: https://doi.org/10.1007/978-3-642-12808-0_4
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