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Genetic Programming and Evolvable Machines
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Current network protocols must comply with rigid interfaces and rules of behavior to fit into well defined, vertical protocol stacks. It is difficult for network designers to offer a wide spectrum of alternative protocols suitable for diverse situations, and to make the stack evolve to match new needs. The tendency is to design protocols that can adapt to the widest possible spread of use. However, even the best adaptive protocols cannot possibly cope with all situations. When their adaptivity limits are reached, the ability to switch to other protocols becomes a clear advantage Our aim in this paper is to present Lightweight Autonomous resIlient Networks (LAIN), a framework that exploits the multiplicity of alternative protocol, and exposes the spectrum of choice to the advantage of the applications. The system runs continuous experiments with alternative protocols online, in parallel as well as serially, in order to select automatically those that best match the application's needs under the current network conditions. We report first results on the feasibility of the approach and point out the need for such a system in network and protocol evolution