Ontology for Knowledge Graphs of Telecommunication Network Monitoring Systems

Kulikov, Igor; Vodyaho, Alexander; Stankova, Elena N.; Zhukova, Nataly

doi:10.1007/978-3-030-87010-2_32

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Moreover, Silva et al have presented an ontology that allows defining a network measurement topology and sampling techniques to enable context-aware network monitoring [49]. Multiple other approaches focus specifically on designing an ontology for telecommunications network management and monitoring [50][51][52].…”

Section: Monitoring Ontologiesmentioning

confidence: 99%

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

De Brouwer,

De Turck,

Ongenae

2024

J Netw Syst Manage

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In the Internet of Things (IoT), semantic IoT platforms are often used to solve the challenges associated with the real-time integration of heterogeneous IoT sensor data, domain knowledge and context information. Existing platforms mostly have a static distribution and configuration of queries deployed on the platform's stream processing components. In contrast, the environmental context in which queries are deployed has a very dynamic nature: real-world set-ups involve varying tasks, device resource usage, networking conditions, etc. To solve this mismatch, this paper presents DIVIDE, an IoT platform component built on Semantic Web technologies. DIVIDE has a generic design containing multiple subcomponents that monitor the environment across a cascading architecture. By monitoring the use case context, DIVIDE adaptively derives the appropriate stream processing queries in a context-aware way. Using a Local Monitor deployed on edge devices, situational context parameters are measured and aggregated. The Meta Model allows modeling these measurements, and meta-information about devices and deployed stream processing queries. Through the definition of application-specific Global Monitor queries that are continuously evaluated centrally on the Meta Model, end users can dynamically configure how the situational context should influence the window parameter configuration and distribution of queries in the network. The paper evaluates a first implementation of DIVIDE on a homecare monitoring use case. The results show how DIVIDE can successfully adapt to varying device and networking conditions, taking into account the use case requirements. This way, DIVIDE allows better balancing use case specific trade-offs and achieves more efficient stream processing.

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Section: Monitoring Ontologiesmentioning

confidence: 99%

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

De Brouwer,

De Turck,

Ongenae

2024

J Netw Syst Manage

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“…Graph-based reasoning involves traversing nodes and edges in the graph to explore relationships between entities. Examples of such formalisms are knowledge graphs, ontologies, and semantic networks [14,15].…”

Section: Graph-based Formalismsmentioning

confidence: 99%

An Evaluation Survey of Knowledge-Based Approaches in Telecommunication Applications

Koudouridis,

Shalmashi,

Moosavi

2024

Telecom

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The purpose of this survey study is to shed light on the importance of knowledge usage and knowledge-driven applications in telecommunication systems and businesses. To this end, we first define a classification of the different knowledge-based approaches in terms of knowledge representations and reasoning formalisms. Further, we define a set of qualitative criteria and evaluate the different categories for their suitability and usefulness in telecommunications. From the evaluation results, we could conclude that different use cases are better served by different knowledge-based approaches. Further, we elaborate and showcase our findings on three different knowledge-based approaches and their applicability to three operational aspects of telecommunication networks. More specifically, we study the utilization of large language models in network operation and management, the automation of the network based on knowledge-graphs and intent-based networking, and the optimization of the network based on machine learning-based distributed intelligence. The article concludes with challenges, limitations, and future steps toward knowledge-driven telecommunications.

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Performing First-Order-Logic Queries Over RDF Data: Interpreter Versus Compiler to Apache Jena Rules

Krygin,

Karpenko,

Sychev

2024

Lecture Notes in Networks and Systems

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Ontology for Knowledge Graphs of Telecommunication Network Monitoring Systems

Cited by 3 publications

References 18 publications

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

Enabling Efficient Semantic Stream Processing Across the IoT Network Through Adaptive Distribution with DIVIDE

An Evaluation Survey of Knowledge-Based Approaches in Telecommunication Applications

Performing First-Order-Logic Queries Over RDF Data: Interpreter Versus Compiler to Apache Jena Rules

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