FlowMaster: Early Eviction of Dead Flow on SDN Switches

High performance switches employ extremely low latency memory subsystems in an effort to reap the lowest feasible end-to-end flow level latencies. Their capacities are extremely valuable as the size of these memories is limited due to several architectural constraints such as power and silicon area....

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Published inDistributed Computing and Networking pp. 484 - 498
Main Authors Kannan, Kalapriya, Banerjee, Subhasis
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2014
SeriesLecture Notes in Computer Science
Online AccessGet full text
ISBN3642452485
9783642452482
ISSN0302-9743
1611-3349
DOI10.1007/978-3-642-45249-9_32

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Abstract High performance switches employ extremely low latency memory subsystems in an effort to reap the lowest feasible end-to-end flow level latencies. Their capacities are extremely valuable as the size of these memories is limited due to several architectural constraints such as power and silicon area. This necessity is further exacerbated with the emergence of Software Defined Networks (SDN) where fine-grained flow definitions lead to explosion in the number of flow entries. In this paper, we propose FlowMaster, a speculative mechanism to update the flow table by predicting when an entry becomes stale and evict the same early to accommodate new entries. We collage the observations from predictors into a Markov based learning predictor that predicts whether a flow is valuable any more. Our experiments confirm that FlowMaster enables efficient usage of flow tables thereby reducing the discard rate from flow table by orders of magnitude and in some cases, eliminating discards completely.
AbstractList High performance switches employ extremely low latency memory subsystems in an effort to reap the lowest feasible end-to-end flow level latencies. Their capacities are extremely valuable as the size of these memories is limited due to several architectural constraints such as power and silicon area. This necessity is further exacerbated with the emergence of Software Defined Networks (SDN) where fine-grained flow definitions lead to explosion in the number of flow entries. In this paper, we propose FlowMaster, a speculative mechanism to update the flow table by predicting when an entry becomes stale and evict the same early to accommodate new entries. We collage the observations from predictors into a Markov based learning predictor that predicts whether a flow is valuable any more. Our experiments confirm that FlowMaster enables efficient usage of flow tables thereby reducing the discard rate from flow table by orders of magnitude and in some cases, eliminating discards completely.
Author Banerjee, Subhasis
Kannan, Kalapriya
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Chatterjee, Mainak
Rajsbaum, Sergio
Kothapalli, Kishore
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Snippet High performance switches employ extremely low latency memory subsystems in an effort to reap the lowest feasible end-to-end flow level latencies. Their...
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Title FlowMaster: Early Eviction of Dead Flow on SDN Switches
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