A knowledge graph based construction method for Digital Twin Network
Yanhong Zhu, Danyang Chen, Cheng Zhou, Lu Lu, Xiaodong Duan
Abstract
With the advent of the digital age, digital twin as a new potential technology has received much attention from both academia and industry increasingly. Digital twin technology paves a way for achieving cost-efficient trial and performance-optimal management, through creating a virtual representation of physical network digitally to simulate and predict. In this paper, we propose a novel network paradigm, called digital twin network (DTN) architecture for the future network, which consists of Physical Network, Data Lake, Digital Twin Layer and Network Application Layer. A Sketch acquisition algorithm is introduced to meet the demand of large-scale real-time data collection in Data Lake. A digital twin network construction method based on knowledge graph is developed, which can represent entity attribute and various topologies according to physical network. Finally, the proposed DTN is introduced to realize fault self-healing in the future network, and the feasibility and novelty is proved.