Abstract
Nowadays Network Configuration Protocol (NETCONF) has become an essential part of network management for its flexibility and scalability. Vendors intend to use NETCONF to replace Command-Line Interface (CLI) and Simple Network Management Protocol (SNMP) to manage devices. Yet Another Next Generation (YANG) models are tailored to model NETCONF protocol messages. However, there exists heterogeneity issue with YANG models as a consequence of vendors proposing proprietary YANG models which differ from each other in structure or content. Thus, managing network devices from different vendors requires expert knowledge and plenty of resources. In this paper, we present MAYA, a solution to automatically accomplish alignment of YANG models from different vendors or organizations by exploring multiform node attributes. In MAYA, different semantic similarity techniques are used to measure distance between different attributes, such as name, description and type, in nodes from various YANG models. A customized SMP based matching algorithm for YANG models alignment is proposed to generate mapping relations between models based on the semantic similarity. The real cases analysis and experiments show that MAYA is able to meet the demands in production on the problem of YANG model alignment.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.