{"id":"https://openalex.org/W3088630677","doi":"https://doi.org/10.1109/eucnc48522.2020.9200910","title":"Predicting Bandwidth Utilization on Network Links Using Machine Learning","display_name":"Predicting Bandwidth Utilization on Network Links Using Machine Learning","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3088630677","doi":"https://doi.org/10.1109/eucnc48522.2020.9200910","mag":"3088630677"},"language":"en","primary_location":{"id":"doi:10.1109/eucnc48522.2020.9200910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eucnc48522.2020.9200910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 European Conference on Networks and Communications (EuCNC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2112.02417","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073274232","display_name":"Maxime Labonne","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085861","display_name":"Laboratoire d'Int\u00e9gration des Syst\u00e8mes et des Technologies","ror":"https://ror.org/000dbcc61","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210085861","https://openalex.org/I4210117989"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Maxime Labonne","raw_affiliation_strings":["Institut LIST, Palaiseau, France","LSC - Laboratoire des Syst\u00e8mes Communicants (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut LIST, Palaiseau, France","institution_ids":["https://openalex.org/I4210085861"]},{"raw_affiliation_string":"LSC - Laboratoire des Syst\u00e8mes Communicants (France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050531178","display_name":"Charalampos Chatzinakis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085861","display_name":"Laboratoire d'Int\u00e9gration des Syst\u00e8mes et des Technologies","ror":"https://ror.org/000dbcc61","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210085861","https://openalex.org/I4210117989"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Charalampos Chatzinakis","raw_affiliation_strings":["Institut LIST, Palaiseau, France","LSC - Laboratoire des Syst\u00e8mes Communicants (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut LIST, Palaiseau, France","institution_ids":["https://openalex.org/I4210085861"]},{"raw_affiliation_string":"LSC - Laboratoire des Syst\u00e8mes Communicants (France)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084246022","display_name":"Alexis Olivereau","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085861","display_name":"Laboratoire d'Int\u00e9gration des Syst\u00e8mes et des Technologies","ror":"https://ror.org/000dbcc61","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210085861","https://openalex.org/I4210117989"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Alexis Olivereau","raw_affiliation_strings":["Institut LIST, Palaiseau, France","LSC - Laboratoire des Syst\u00e8mes Communicants (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut LIST, Palaiseau, France","institution_ids":["https://openalex.org/I4210085861"]},{"raw_affiliation_string":"LSC - Laboratoire des Syst\u00e8mes Communicants (France)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210085861"],"apc_list":null,"apc_paid":null,"fwci":0.4507,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.5181764,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"242","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12326","display_name":"Network Packet Processing and Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12326","display_name":"Network Packet Processing and Optimization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10138","display_name":"Network Traffic and Congestion Control","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8476556539535522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8337029218673706},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.6956058740615845},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5842934250831604},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5717827081680298},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5180680751800537},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5162367820739746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4794294238090515},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4657958745956421},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4355069100856781},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4137089252471924},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33485597372055054},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3225680887699127},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.318434476852417},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1914767324924469}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8476556539535522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8337029218673706},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.6956058740615845},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5842934250831604},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5717827081680298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5180680751800537},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5162367820739746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4794294238090515},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4657958745956421},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4355069100856781},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4137089252471924},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33485597372055054},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3225680887699127},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.318434476852417},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1914767324924469},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/eucnc48522.2020.9200910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eucnc48522.2020.9200910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 European Conference on Networks and Communications (EuCNC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2112.02417","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2112.02417","pdf_url":"https://arxiv.org/pdf/2112.02417","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:cea-04598213v1","is_oa":true,"landing_page_url":"https://cea.hal.science/cea-04598213","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/document/9200910","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:HAL:hal-04597794v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04597794","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 European Conference on Networks and Communications (EuCNC), Jun 2020, Dubrovnik, France. pp.242-247, &#x27E8;10.1109/EuCNC48522.2020.9200910&#x27E9;","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2112.02417","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2112.02417","pdf_url":"https://arxiv.org/pdf/2112.02417","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1517808374","https://openalex.org/W1597623201","https://openalex.org/W1608999459","https://openalex.org/W1835640267","https://openalex.org/W2029375645","https://openalex.org/W2064675550","https://openalex.org/W2073752908","https://openalex.org/W2118026781","https://openalex.org/W2159262496","https://openalex.org/W2809011885","https://openalex.org/W2964804115","https://openalex.org/W2978866625","https://openalex.org/W2998678080","https://openalex.org/W3020993522","https://openalex.org/W4205146804","https://openalex.org/W4299589157","https://openalex.org/W4300945730","https://openalex.org/W6630956611","https://openalex.org/W6636558983","https://openalex.org/W6669144474","https://openalex.org/W6677823972"],"related_works":["https://openalex.org/W3175321409","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W4391216528","https://openalex.org/W4312309719","https://openalex.org/W2980748541","https://openalex.org/W4313123484","https://openalex.org/W2146461990","https://openalex.org/W4200142652"],"abstract_inverted_index":{"Predicting":[0],"the":[1,31,53,56,107,132,138],"bandwidth":[2,32,109],"utilization":[3,33],"on":[4,59],"network":[5,36,45,57],"links":[6,37,58],"can":[7,141],"be":[8,142],"extremely":[9],"useful":[10],"for":[11,127,131],"detecting":[12],"congestion":[13],"in":[14,71,103,144],"order":[15,72,104],"to":[16,29,48,52,73,105],"correct":[17],"them":[18],"before":[19],"they":[20],"occur.":[21],"In":[22],"this":[23],"paper,":[24],"we":[25],"present":[26],"a":[27,39,75,123,148,152],"solution":[28,140],"predict":[30,106],"between":[34],"different":[35],"with":[38,68,117,147],"very":[40,118],"high":[41],"accuracy.":[42],"A":[43],"simulated":[44],"is":[46],"created":[47],"collect":[49],"data":[50,63],"related":[51],"performance":[54],"of":[55,84],"every":[60],"interface.":[61],"These":[62],"are":[64],"processed":[65],"and":[66,80,98,115,129],"expanded":[67],"feature":[69],"engineering":[70],"create":[74],"training":[76],"set.":[77],"We":[78,134],"evaluate":[79],"compare":[81],"three":[82],"types":[83],"machine":[85],"learning":[86],"algorithms,":[87],"namely":[88],"ARIMA":[89,114,128],"(AutoRegressive":[90],"Integrated":[91],"Moving":[92],"Average),":[93],"MLP":[94,116],"(Multi":[95],"Layer":[96],"Perceptron)":[97],"LSTM":[99,112],"(Long":[100],"Short-Term":[101],"Memory),":[102],"future":[108],"consumption.":[110],"The":[111],"outperforms":[113],"accurate":[119],"predictions,":[120],"rarely":[121],"exceeding":[122],"3%":[124],"error":[125],"(40%":[126],"20%":[130],"MLP).":[133],"then":[135],"show":[136],"that":[137],"proposed":[139],"used":[143],"real":[145],"time":[146],"reaction":[149],"managed":[150],"by":[151],"Software-Defined":[153],"Networking":[154],"(SDN)":[155],"platform.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
