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Autonomic Network Applications Designed after Immunological Self-Regulatory Adaptation

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2 Author(s)
Chonho Lee ; Department of Computer Science, University of Massachusetts, Boston. ; Junichi Suzuki

As Internet applications have been rapidly increasing in complexity and scale, they are expected to be autonomous and adaptive to dynamic changes in the network. Based on the observation that various biological systems have already overcome these requirements, this paper describes a biologically-inspired framework, called iNet, to design autonomous and adaptive Internet applications. It is designed after the mechanisms behind how the immune system detects antigens (e.g., viruses), specifically produces antibodies to eliminate them, and self-regulates the production of antibodies against its anomaly (e.g., immunodeficiency and autoimmunity). iNet models a set of environment conditions (e.g., network traffic and resource availability) as an antigen and a behavior of applications (e.g., migration and reproduction) as an antibody. iNet allows each application to autonomously sense its surrounding environment conditions (i.e., an antigen) to evaluate whether it adapts well to the sensed conditions based on an evaluation policy, and if it does not, adaptively invoke a behavior (i.e., an antibody) suitable for the conditions. iNet also allows each application to dynamically configure its own evaluation policy so that it can trigger the behavior invocation at the right time. Simulation results show that iNet allows applications to autonomously adapt to changing environment conditions and to dynamically self-regulate the behavior invocation by configuring the evaluation policy when the evaluation fails

Published in:

2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems

Date of Conference:

April 30 2007-May 3 2007