Autonomic Adaptation of Network Applications with the iNet Artificial Immune System

C. Lee and J. Suzuki (USA)


Autonomous adaptive networks, artificial immune system


This paper describes and empirically evaluates a biologi cally-inspired adaptation mechanism that allows network applications to autonomously adapt to dynamic environ ment changes in the network. Based on the observation that the immune system has elegantly achieved autono mous adaptation, the proposed mechanism, called the iNet artificial immune system, follows the mechanisms behind how the immune system detects antigens (e.g. viruses) and specifically reacts to them. iNet models a behavior of network applications (e.g. migration and replication) as an antibody, and an environment condition (e.g. network traffic and resource availability) as an antigen. iNet allows each network application to autonomously sense its local environment conditions (i.e. antigens) to evaluate whether it adapts well to the sensed conditions, and if it does not, adaptively perform a behavior (i.e. antibody) suitable for the conditions. Measurement results show iNet works effi ciently and makes network applications adaptive.

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