Sareari adimena gehitzen: machine learning eta gaitasun kognitiboen sarrera sare-mailako monitorizaziorako eta matxuren diagnostikorako

Abstract

The specific characteristics of next generation networks entail the impossibility of a proper management according to the conventional networking models, due to their inability to adjust the scale, the heterogeneity and the complexity of those scenarios. Therefore, it is necessary to define new paradigms to design and manage these emergent communication systems. At this point, adding cognitive capabilities to the network through the application of machine learning techniques makes it possible to leverage the protocol information that travels along the network attached to the data. This data is use to infer information about the state of the network and exploit it to prevent dysfunctions and improve the overall performance. This paper introduces the design of an intelligent module integrated at network level, based on offline machine learning, to gather and interpret information to complement and support the routing functionality. This context-aware cognitive module manipulates the behaviour of the routing protocol depending on the monitored state of the network to avoid failures, balance the traffic and get a global enhancement.