<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.perlman-trill-smart-endnodes" target="https://datatracker.ietf.org/doc/html/draft-perlman-trill-smart-endnodes-04">
   <front>
      <title>TRILL Smart Endnodes</title>
      <author initials="R." surname="Perlman" fullname="Radia Perlman">
         <organization>Intel Labs</organization>
      </author>
      <author initials="F." surname="hu" fullname="fangwei hu">
         <organization>ZTE Corporation</organization>
      </author>
      <author initials="D. E." surname="Eastlake" fullname="Donald E. Eastlake 3rd">
         <organization>Dell</organization>
      </author>
      <author initials="K. V." surname="Krupakaran" fullname="Kesava Vijaya Krupakaran">
         <organization>Dell</organization>
      </author>
      <author initials="T." surname="Liao" fullname="Ting Liao">
         <organization>ZTE Corporation</organization>
      </author>
      <date month="October" day="17" year="2014" />
      <abstract>
	 <t>   This draft addresses the problem of the size and freshness of the
   endnode learning table in edge RBridges, by allowing endnodes to
   volunteer for endnode learning and encapsulation/decapsulation.  Such
   an endnode is known as a &quot;smart endnode&quot;.  Only the attached RBridge
   can distinguish a &quot;smart endnode&quot; from a &quot;normal endnode&quot;.  The smart
   endnode uses the nickname of the attached RBridge, so this solution
   does not consume extra nicknames.  The solution also enables Fine
   Grained Label aware endnodes.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-perlman-trill-smart-endnodes-04" />
   
</reference>
