6533b7d5fe1ef96bd12651cc

RESEARCH PRODUCT

Embedding Evolution in Epidemic-Style Forwarding

Daniele MiorandiGiovanni NegliaIacopo CarrerasSara Alouf

subject

Scheme (programming language)Theoretical computer scienceComputer scienceSurvival of the fittestNode (networking)Quality control and genetic algorithmsProcess (computing)Quantitative Biology::Genomics[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]EmbeddingQuantitative Biology::Populations and EvolutioncomputerSelection (genetic algorithm)computer.programming_language

description

International audience; In this work, we introduce a framework to let forwarding schemes evolve in order to adapt to changing and a priori unknown environments. The framework is inspired by genetic algorithms: at each node a genotype describes the forwarding scheme used, a selection process fosters the diffusion of the fittest genotypes in the system and new genotypes are created by combining existing ones or applying random changes. A case study implementation is presented and its performance evaluated via numerical simulations.

yearjournalcountryeditionlanguage
2007-10-08
10.1109/mobhoc.2007.4428686https://hal.inria.fr/hal-00641273/document