Cognitive Network Framework for Heterogeneous Wireless Networks

The Internet is used by more than two billion customers around the world and is expected to serve as a global platform for interconnecting cyber-physical objects that form the Internet of Things (IoT). Within the next decade, traffic demands are expected to increase a thousand-fold. This challenge can be addressed by introducing and expanding heterogeneous wireless technologies, which provide higher network capacity, wider coverage and higher quality of service (QoS). However, the heterogeneity and complexity of these networks are a major challenge for traditional control and management systems. Therefore, there is a need for self-manageable and self-configurable networks that support the data produced by the different IoT devices and provide opportunities for data analytics. In this work, a cognitive network framework is proposed, in which the network protocol stack is integrated with a semantic system. The proposed framework provides the bases for building smart networks that observe data from different layers in the network protocol stack and represents it in a hierarchical structure in a knowledge base. The framework employs an ontology that provides an abstraction model for the different heterogeneous wireless devices. The ontology determines the relationships between technology-dependent parameters in the network protocol stack and enables, through the use of inferences, the utilization of the observed data from the network. The use of a cognitive network framework with the network protocol stack allows adding ontologies to describe the data, a solution which could solve the problem of analysing, searching or visualising data.