Name
Abstract | ||
|---|---|---|
Advanced automation is needed in future mobile networks to provide adequate service quality economically and with high reliability. In this paper, a system is presented that takes into account the network context, analyses uncertain information, and infers network configurations by means of probabilistic reasoning. The system introduced in this paper is an experimental platform integrating a mobile network simulator, a Markov Logic Network (MLN) model, and an OWL 2 ontology into a runtime environment that can be monitored via a Resource Description Framework (RDF) - based user interface. In this approach, the OWL ontology contains a semantic representation of the relevant concepts, and the MLN model evaluates elements of uncertain information. Experiments based on a prototype implementation demonstrate the value of semantic modelling and probabilistic reasoning in network status characterization, optimization, and visualization. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3233/AIS-160419 | JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS |
Keywords | Field | DocType |
Network management,5G,semantic modelling,probabilistic reasoning,ontologies,Markov Logic Networks | Ontology (information science),Ontology,Computer science,Probabilistic CTL,Artificial intelligence,Probabilistic argumentation,Probabilistic logic,Reasoning system,Network management,Machine learning | Journal |
Volume | Issue | ISSN |
9 | 1 | 1876-1364 |
Citations | PageRank | References |
3 | 0.55 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kasper Apajalahti | 1 | 5 | 1.96 |
| Eero Hyvönen | 2 | 843 | 103.43 |
| Juha Niiranen | 3 | 5 | 1.62 |
| Räisänen, V. | 4 | 4 | 2.95 |