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NetREC: Network-wide in-network REal-value Computation


The current generation of networks empowers the use of programmable switches whose behaviour can be defined using languages like P4. Nevertheless, these languages do not support network-wide deployment of stateful real-value functions. This paper presents NetREC, an extension of RMT programmable data planes designed to enable stateful real-value functions computation across multiple switches. NetREC first decomposes the real-value functions into a dependency graph of elementary operations that are distributed among the network. This distribution is carried out by dynamically generating and solving an integer linear program. We deploy a prototype of NetREC on a network of Tofino switches and demonstrate its capability of computing recursive real-value functions like exponential weighted moving average.
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Dates and versions

hal-03794892 , version 1 (03-10-2022)


  • HAL Id : hal-03794892 , version 1


Matthews Jose, Kahina Lazri, Jérôme François, Olivier Festor. NetREC: Network-wide in-network REal-value Computation. IEEE NetSoft 2022 - 8th IEEE International Conference on Network Softwarization, Jun 2022, Milan, Italy. ⟨hal-03794892⟩
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