Towards a Model for Quantitative Reasoning in Cognitive Nodes

Cognitive networks are proposed in the framework of evolution of network architectures as novel paradigms to provide autonomous in-network reasoning to support end-to-end goals. While several approaches are available that propose different approaches, still the problem of reasoning represents a challenging issue. The paper aims at proposing a mathematical model, based on fuzzy cognitive maps, to support and provide a quantitative tool for implementing reasoning in nodes of a cognitive network. In particular, the idea is to provide a methodology to enable network nodes to represent the complex interactions that happen within their protocol stacks and across the network. The potential utility of the proposed scheme is then preliminarily validated on a sample scenario, outlining good results and relevant potential for future developments.