NetSketch: Automated network configuration from hand-drawn topologies
Lu, Yuantao
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https://hdl.handle.net/2142/122264
Description
Title
NetSketch: Automated network configuration from hand-drawn topologies
Author(s)
Lu, Yuantao
Issue Date
2023-12-05
Director of Research (if dissertation) or Advisor (if thesis)
Caesar, Matthew Chapman
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Hand-drawn Diagrams
Computer Vision
Network Synthesis
Language
eng
Abstract
Designing and configuring computer networks can be a complex and time-consuming process, often requiring expert knowledge and specialized tools. With the growing demand for more intuitive and efficient network design methodologies, this thesis explores the possibilities of computer vision technology as a solution. Specifically, this research seeks to address the following question: Can we simplify the network design process by utilizing computer vision technology to recognize hand-drawn computer networks and configure them automatically? We propose NetSketch, a novel system that integrates modern object detection techniques with classic image gradient-based computer vision algorithms. This system identifies network components from hand-drawn diagrams and employs network synthesis algorithms to automatically generate correct and resilient network models. Based on our evaluation, our network vision framework demonstrates over 99.5% accuracy in detecting network components and network links from hand-drawn diagrams. In addition, our vision synthesis component always generates configurations that meet network design requirements, leading to more efficient network planning and management. This work has the potential to improve network design processes, making them more intuitive and efficient, with applications in network management, education, and collaboration.
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