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Fitting genetic algorithms to distributed online evolution of network protocols

Abstract : In this work, we introduce a framework for enabling the on-line evolution of network protocols. The proposed approach is based on the use of techniques and tools drawn from evolutionary computing research, and it enables embedding evolutionary features in the operation of network protocols. In this way, it becomes possible to build a system in which the operation of the network changes at run-time to adapt to the current conditions. As a case study, we apply the proposed framework to the evolution of forwarding schemes in intermittently connected wireless networks. Simulation results are reported to validate the ability of the proposed scheme to converge to the optimal operating point and to explore the various trade-offs deriving from its design and implementation.
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Sara Alouf, Giovanni Neglia, Iacopo Carreras, Daniele Miorandi, Álvaro Fialho. Fitting genetic algorithms to distributed online evolution of network protocols. Computer Networks, Elsevier, 2010, 54 (18), pp.3402-3420. ⟨10.1016/j.comnet.2010.06.015⟩. ⟨hal-00640798⟩



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