Combining ontologies and markov logic networks for statistical relational mobile network analysis

Abstract

Mobile networks are managed by means of operations support systems (OSS) which facilitate performance, fault, and configuration management. Network complexity is increasing due to the heterogeneity of cell types, devices, and applications. Characterization and configuration of networks optimally in such a scenario is challenging task. This paper introduces an experimental platform that combines statistical relational learning and semantic technologies by integrating a mobile network simulator, Markov Logic Network model (MLN) and an OWL 2 ontology into a runtime environment tool. Our experiments, based on a prototype implementation, indicate that the combination of an ontology and MLN model can be utilized in network status characterization, optimization and visualization.