An ontology-based recommendation system for context-aware network monitoring

Abstract

Current network management systems urge for a context-aware perspective of the provided network services and the underlying infrastructure usage. This need results from the heterogeneity of services and technologies in place, and from the massive traffic volumes traversing today’s networks. To reduce complexity and improve interoperability, monitoring systems need to be flexible, context-aware, and able to self-configure measurement points (MPs) according to network monitoring tasks requirements. In addition, the use of sampling techniques in MPs to reduce the amount of traffic collected, analysed and stored has become mandatory and, currently, distinct sampling schemes are available for use in operational environments. In this context, the main objective of this paper is the ontological definition of measurement requirements and components in sampling-based monitoring environments, with the aim of supporting an expert recommendation system able to understand context and identify the appropriate configuration rules to apply to a selection of MPs. In this way, the ontology, defining management needs, network measurement topology and sampling techniques, is described and explored considering several network management activities. A use case focusing on traffic accounting as monitoring task is also provided, demonstrating the expressiveness of the ontology and the role of the recommendation system in assisting context-aware network monitoring based on traffic sampling. © Springer Nature Switzerland AG 2019.