Self-adaptive networks with history extrapolation, evolutionary selection and realtime response

The Self Adaptive Evolutionary Network (SAEN) architecture proposes a modern approach on resource utilization by combining load-balancing technologies, history behavior analysis and genetic algorithms for enforcing the optimal routing solution. Unlike traditional routing in which the next-hop decision is done at the transited node, SAEN proposes a holistic routing system with the help of classifiers. Optimal solutions are being evaluated according to their history. The search is done with a genetic algorithms that uses adaptive operators (crossover, mutation). Each chromosome is scored by the fitness function. Based on its history, it is possible to predict how a certain link will behave, ahead of time.