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Leveraging in-network real-value computation for home network device recognition

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Abstract

Current generation of switches are highly programmable and able to support stateful. However, these switches cannot perform floating point operations. As a result several network applications have to be run on external servers or middleboxes in the network. We introduce InREC, a system that extends the capabilities of programmable switches to support in-network real-valued operations using the IEEE half-precision floating point representation. Our demo on a Barefoot Tofino switches demonstrates the efficiency of InREC for in-network computation by computing a logistic regression function to classify devices (IoT and laptop) in a simulated home environment.
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Dates and versions

hal-03525070 , version 1 (13-01-2022)

Identifiers

  • HAL Id : hal-03525070 , version 1

Cite

Matthews Jose, Kahina Lazri, Jérôme François, Olivier Festor. Leveraging in-network real-value computation for home network device recognition. IM 2021 - IFIP/IEEE International Symposium on Integrated Network Management (Demo), May 2021, Bordeaux / Virtual, France. ⟨hal-03525070⟩
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