Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385227024> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W4385227024 abstract "Delivering perfectly alright real-time traffic information is crucial for managing a wide range of networks, particularly vehicular communications, anomaly analysis, networking accounting, and available bandwidth. Application networking might be able to give fine-grained evaluation by offering details for each sent rules of just an Open circulation switching. Providing absolutely adequate real-time traffic information in hardware switches also poses serious problems because of the size constraints of TCAMs that can only accommodate a minimal number of rules in contrast to the number of current fluxes in the networks. Inside this editorial, we initiate Intense Flow going, a scheme for modular app assessing that's also premised on an efficient method that a) flexibly senses the channel's highest traffic references and locations prefixes, b) collects coarse-grained stream size readings for less energetic identifiers and perfectly alright metrics for the more engaged users; c) includes historical metrics to coach a cloud-based a profound learners model that has the potential to create short forecasts anytime precise f Due to the lack of the need for additional flow sampling methods that compromise accuracy, a large increase in the number of totally acceptable flows that may be recorded is now possible. . Deep Flowing can provide incredibly high accuracy for estimating flow quantities at various hierarchy levels, according to a rigorous experimental analysis using a prototype versions and actual networking signals." @default.
- W4385227024 created "2023-07-25" @default.
- W4385227024 creator A5011020166 @default.
- W4385227024 creator A5020807267 @default.
- W4385227024 creator A5077471037 @default.
- W4385227024 creator A5079111994 @default.
- W4385227024 creator A5092528961 @default.
- W4385227024 creator A5092533459 @default.
- W4385227024 date "2023-05-12" @default.
- W4385227024 modified "2023-10-14" @default.
- W4385227024 title "Deepflow: A Software-Defined Measurement System for Deep Learning" @default.
- W4385227024 cites W2000300202 @default.
- W4385227024 cites W2040340473 @default.
- W4385227024 cites W2047627502 @default.
- W4385227024 cites W2064675550 @default.
- W4385227024 cites W2094287084 @default.
- W4385227024 cites W2112320294 @default.
- W4385227024 cites W2116609512 @default.
- W4385227024 cites W2126822952 @default.
- W4385227024 cites W2140426549 @default.
- W4385227024 cites W2154965732 @default.
- W4385227024 cites W2169486379 @default.
- W4385227024 cites W2487095677 @default.
- W4385227024 cites W2530137915 @default.
- W4385227024 cites W2775501751 @default.
- W4385227024 cites W3092362704 @default.
- W4385227024 cites W3119980894 @default.
- W4385227024 cites W3126135128 @default.
- W4385227024 cites W4248708867 @default.
- W4385227024 cites W4285815612 @default.
- W4385227024 cites W4362496348 @default.
- W4385227024 cites W4362496529 @default.
- W4385227024 doi "https://doi.org/10.1109/icacite57410.2023.10182469" @default.
- W4385227024 hasPublicationYear "2023" @default.
- W4385227024 type Work @default.
- W4385227024 citedByCount "0" @default.
- W4385227024 crossrefType "proceedings-article" @default.
- W4385227024 hasAuthorship W4385227024A5011020166 @default.
- W4385227024 hasAuthorship W4385227024A5020807267 @default.
- W4385227024 hasAuthorship W4385227024A5077471037 @default.
- W4385227024 hasAuthorship W4385227024A5079111994 @default.
- W4385227024 hasAuthorship W4385227024A5092528961 @default.
- W4385227024 hasAuthorship W4385227024A5092533459 @default.
- W4385227024 hasConcept C101468663 @default.
- W4385227024 hasConcept C111919701 @default.
- W4385227024 hasConcept C120314980 @default.
- W4385227024 hasConcept C127162648 @default.
- W4385227024 hasConcept C154504017 @default.
- W4385227024 hasConcept C162324750 @default.
- W4385227024 hasConcept C2777904410 @default.
- W4385227024 hasConcept C31170391 @default.
- W4385227024 hasConcept C31258907 @default.
- W4385227024 hasConcept C34447519 @default.
- W4385227024 hasConcept C41008148 @default.
- W4385227024 hasConcept C77270119 @default.
- W4385227024 hasConcept C79403827 @default.
- W4385227024 hasConcept C79974875 @default.
- W4385227024 hasConceptScore W4385227024C101468663 @default.
- W4385227024 hasConceptScore W4385227024C111919701 @default.
- W4385227024 hasConceptScore W4385227024C120314980 @default.
- W4385227024 hasConceptScore W4385227024C127162648 @default.
- W4385227024 hasConceptScore W4385227024C154504017 @default.
- W4385227024 hasConceptScore W4385227024C162324750 @default.
- W4385227024 hasConceptScore W4385227024C2777904410 @default.
- W4385227024 hasConceptScore W4385227024C31170391 @default.
- W4385227024 hasConceptScore W4385227024C31258907 @default.
- W4385227024 hasConceptScore W4385227024C34447519 @default.
- W4385227024 hasConceptScore W4385227024C41008148 @default.
- W4385227024 hasConceptScore W4385227024C77270119 @default.
- W4385227024 hasConceptScore W4385227024C79403827 @default.
- W4385227024 hasConceptScore W4385227024C79974875 @default.
- W4385227024 hasLocation W43852270241 @default.
- W4385227024 hasOpenAccess W4385227024 @default.
- W4385227024 hasPrimaryLocation W43852270241 @default.
- W4385227024 hasRelatedWork W1882848237 @default.
- W4385227024 hasRelatedWork W2130966263 @default.
- W4385227024 hasRelatedWork W2316776327 @default.
- W4385227024 hasRelatedWork W2328387788 @default.
- W4385227024 hasRelatedWork W2383532021 @default.
- W4385227024 hasRelatedWork W2390777183 @default.
- W4385227024 hasRelatedWork W2911510094 @default.
- W4385227024 hasRelatedWork W2996877075 @default.
- W4385227024 hasRelatedWork W4252772812 @default.
- W4385227024 hasRelatedWork W4313054100 @default.
- W4385227024 isParatext "false" @default.
- W4385227024 isRetracted "false" @default.
- W4385227024 workType "article" @default.