Building and Applying Knowledge Graph in Edge Analytics Environment

Abstract For the scenario of limited hardware resources and restricted software environment in edge computing architecture, the method of building and applying knowledge graph in edge analytics environment is proposed. The main process includes: building knowledge graph in the cloud, storing knowledge base with RDF format at the edge through customization and transformation, and performing query and analytics at the edge with SPARQL graph search language. The method is simulated in a communication anti-jamming test environment, and the results show that the relevant technical solutions can better meet the requirements of construction of knowledge graph and data analysis in a restricted edge analytics environment.