<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.lee-teas-actn-pm-telemetry-autonomics" target="https://datatracker.ietf.org/doc/html/draft-lee-teas-actn-pm-telemetry-autonomics-17">
   <front>
      <title>YANG models for VN &amp; TE Performance Monitoring Telemetry and Scaling Intent Autonomics</title>
      <author initials="Y." surname="Lee" fullname="Young Lee">
         <organization>Editor</organization>
      </author>
      <author initials="D." surname="Dhody" fullname="Dhruv Dhody">
         <organization>Huawei</organization>
      </author>
      <author initials="S." surname="Karunanithi" fullname="Satish Karunanithi">
         <organization>Huawei</organization>
      </author>
      <author initials="R." surname="Vilalta" fullname="Ricard Vilalta">
         <organization>CTTC</organization>
      </author>
      <author initials="D." surname="King" fullname="Daniel King">
         <organization>Lancaster University</organization>
      </author>
      <author initials="D." surname="Ceccarelli" fullname="Daniele Ceccarelli">
         <organization>Ericsson</organization>
      </author>
      <date month="May" day="8" year="2019" />
      <abstract>
	 <t>   This document provides YANG data models that describe performance
   monitoring telemetry and scaling intent mechanism for TE-tunnels and
   Virtual Networks (VN).

   The models presented in this draft allow customers to subscribe to
   and monitor their key performance data of their interest on the
   level of TE-tunnel or VN. The models also provide customers with the
   ability to program autonomic scaling intent mechanism on the level
   of TE-tunnel as well as VN.



	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-lee-teas-actn-pm-telemetry-autonomics-17" />
   
</reference>
