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UID:420@lincs.fr
DTSTART;TZID=Europe/Paris:20181128T140000
DTEND;TZID=Europe/Paris:20181128T150000
DTSTAMP:20181205T094816Z
URL:https://www.lincs.fr/events/too-many-sdn-rules-compress-them-using-min
 nie/
SUMMARY:Too Many SDN Rules\, Compress Them Using Minnie
DESCRIPTION:Software Defined Networking (SDN) is gaining momentum with the
 support of major manufacturers. While it brings flexibility in the
 management of flows within the data center fabric\, this flexibility comes
 at the cost of smaller routing table capacities. Indeed\, the Ternary
 Content Addressable Memory (TCAM) needed by SDN devices has smaller
 capacities than CAMs used in legacy hardware. To solve this problem\, we
 investigated compression techniques to maximize the utility of SDN switches
 forwarding tables and created MINNIE. MINNIE dynamically compresses SDN
 rules without a noticeable impact on quality of service. We validate our
 solution\, with intensive simulations for well-known data center
 topologies\, to study its efficiency and compression ratio for a large
 number of forwarding rules. Our results indicate that MINNIE scales well\,
 being able to deal with around a million of different flows with less than
 1000 forwarding entry per SDN switch\, requiring negligible computation
 time. To assess the operational viability of MINNIE in real networks\, we
 deployed it on a k = 4 fat-tree data center topology emulated testbed. We
 demonstrate on one hand\, that even with a small number of clients\, the
 limit in terms of number of rules is reached if no compression is
 performed\, increasing the delay of new incoming flows. MINNIE\, on the
 other hand\, reduces drastically the number of rules that need to be
 stored\, with no packet losses\, nor detectable extra delays if routing
 lookups are done in ASICs. Hence\, both simulations and experimental
 results suggest that MINNIE can be safely deployed in real networks\,
 providing compression ratios between 70% and 99%.
CATEGORIES:Seminars,Youtube
LOCATION:LINCS / EIT Digital\, 23 avenue d'Italie\, 75013 Paris\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, 75013
 Paris\, France;X-APPLE-RADIUS=100;X-TITLE=LINCS / EIT Digital:geo:0,0
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TZID:Europe/Paris
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DTSTART:20181028T020000
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