{"id":"https://openalex.org/W4413785978","doi":"https://doi.org/10.1109/ton.2025.3589023","title":"Network Traffic Statistical Upper Limit Prediction From Flow Features for Traffic Fluctuations","display_name":"Network Traffic Statistical Upper Limit Prediction From Flow Features for Traffic Fluctuations","publication_year":2025,"publication_date":"2025-08-28","ids":{"openalex":"https://openalex.org/W4413785978","doi":"https://doi.org/10.1109/ton.2025.3589023"},"language":"en","primary_location":{"id":"doi:10.1109/ton.2025.3589023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2025.3589023","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008404117","display_name":"Erina Takeshita","orcid":"https://orcid.org/0000-0002-9881-3127"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Erina Takeshita","raw_affiliation_strings":["NTT Access Network Service Systems Laboratories, Musashino, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9881-3127","affiliations":[{"raw_affiliation_string":"NTT Access Network Service Systems Laboratories, Musashino, Tokyo, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071318646","display_name":"Tomoya Kosugi","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoya Kosugi","raw_affiliation_strings":["NTT Access Network Service Systems Laboratories, Musashino, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Access Network Service Systems Laboratories, Musashino, Tokyo, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091877740","display_name":"Tomoaki Yoshida","orcid":"https://orcid.org/0000-0002-1673-5293"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Yoshida","raw_affiliation_strings":["NTT Access Network Service Systems Laboratories, Musashino, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-1673-5293","affiliations":[{"raw_affiliation_string":"NTT Access Network Service Systems Laboratories, Musashino, Tokyo, Japan","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008404117"],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23093295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"17","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.954200029373169,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9341999888420105,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/limit","display_name":"Limit (mathematics)","score":0.604631245136261},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5726726055145264},{"id":"https://openalex.org/keywords/speed-limit","display_name":"Speed limit","score":0.4645025432109833},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.4326291084289551},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.43073445558547974},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.42518121004104614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42107075452804565},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4158761501312256},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2731487452983856},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.23500466346740723},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2335643172264099},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.2251027226448059},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2001343071460724},{"id":"https://openalex.org/keywords/mechanics","display_name":"Mechanics","score":0.16706228256225586},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15180382132530212},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.0896061360836029},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.0755733847618103}],"concepts":[{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.604631245136261},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5726726055145264},{"id":"https://openalex.org/C2780210587","wikidata":"https://www.wikidata.org/wiki/Q1077350","display_name":"Speed limit","level":2,"score":0.4645025432109833},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.4326291084289551},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.43073445558547974},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.42518121004104614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42107075452804565},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4158761501312256},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2731487452983856},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23500466346740723},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2335643172264099},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2251027226448059},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2001343071460724},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.16706228256225586},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15180382132530212},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.0896061360836029},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0755733847618103}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ton.2025.3589023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2025.3589023","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1802492819","https://openalex.org/W2064206492","https://openalex.org/W2064675550","https://openalex.org/W2117152787","https://openalex.org/W2171873915","https://openalex.org/W2771644755","https://openalex.org/W2781626870","https://openalex.org/W2808266363","https://openalex.org/W2898017895","https://openalex.org/W2925819646","https://openalex.org/W2947345662","https://openalex.org/W2949104502","https://openalex.org/W2949676527","https://openalex.org/W2961448107","https://openalex.org/W2963432161","https://openalex.org/W2985010893","https://openalex.org/W2989178978","https://openalex.org/W3008924942","https://openalex.org/W3010410179","https://openalex.org/W3013733115","https://openalex.org/W3033989372","https://openalex.org/W3123788679","https://openalex.org/W3171884590","https://openalex.org/W3211407228","https://openalex.org/W4205192696","https://openalex.org/W4206498679","https://openalex.org/W4210368370","https://openalex.org/W4210741861","https://openalex.org/W4220940433","https://openalex.org/W4295934608","https://openalex.org/W4311415873","https://openalex.org/W4315629846","https://openalex.org/W4322706873","https://openalex.org/W4328027885","https://openalex.org/W4376480813","https://openalex.org/W4380885315","https://openalex.org/W4383684407"],"related_works":["https://openalex.org/W2587362999","https://openalex.org/W2149721642","https://openalex.org/W432084041","https://openalex.org/W1977405947","https://openalex.org/W1977153226","https://openalex.org/W4361199786","https://openalex.org/W4239349137","https://openalex.org/W2963251637","https://openalex.org/W1463884142","https://openalex.org/W239469043"],"abstract_inverted_index":{"The":[0,218],"network":[1,7,68],"traffic":[2,21,44,69,112,136,233],"prediction":[3,70,96,146,166,209,243],"is":[4,59,123,184,202,226],"essential":[5],"for":[6,31,39,72,228],"operators":[8],"in":[9,49,152,190,206,213],"cost-effective":[10],"link":[11,29,73,229],"capacity":[12,30,74,230],"planning.":[13],"This":[14],"paper":[15],"proposes":[16],"a":[17,32,67,103,155],"method":[18,71,151,161,183,225],"to":[19,47,93,97,109,186,204],"predict":[20],"statistical":[22],"upper":[23,127],"limits":[24],"(TSUL)":[25],"as":[26,85],"the":[27,40,56,86,111,120,126,145,149,164,181,223,242,247],"required":[28],"planning":[33,57,75,231],"period":[34,58],"of":[35,88,129,148,192,208,215],"several":[36],"months.":[37],"Accounting":[38],"large":[41,139,235],"and":[42,52,90,119,140,163,172,188,198,201,236],"non-stationary":[43,141,237],"fluctuations":[45],"due":[46],"changes":[48],"flow":[50,82,117],"numbers":[51],"bandwidth":[53,91],"needs":[54],"during":[55],"crucial.":[60],"To":[61],"adapt":[62,94],"these":[63],"fluctuations,":[64,142,238],"we":[65,143],"presents":[66],"with":[76,138,154,234],"two":[77],"novelties.":[78],"First,":[79],"it":[80,101],"uses":[81],"features":[83],"such":[84],"number":[87],"flows":[89],"requirements":[92],"TSUL":[95,122,193],"changing":[98],"factors.":[99],"Second,":[100],"utilizes":[102],"Supervised":[104],"Variational":[105],"Auto-Encoder":[106],"(SVAE)":[107],"model":[108,167],"estimate":[110],"probability":[113,157],"density":[114,158],"function":[115,159],"given":[116],"features,":[118],"predicted":[121],"derived":[124],"from":[125],"limit":[128],"its":[130],"confidence":[131],"interval.":[132],"In":[133],"experiments":[134],"using":[135],"data":[137],"evaluate":[144],"accuracy":[147,210,244],"proposed":[150,182,224],"comparison":[153],"linear":[156],"estimation":[160],"(Linear)":[162],"time-series":[165],"(Long":[168],"Short-Term":[169],"Memory:":[170],"LSTM":[171,189],"Temporal":[173],"Fusion":[174],"Transformer:":[175],"TFT).":[176],"Experimental":[177],"results":[178,220],"show":[179],"that":[180,222],"superior":[185,212],"Linear":[187],"terms":[191,207,214],"root":[194],"mean":[195],"square":[196],"error":[197],"log":[199],"likelihood,":[200],"inferior":[203],"TFT":[205],"but":[211,245],"computation":[216,248],"time.":[217],"experimental":[219],"suggest":[221],"suitable":[227],"targeting":[232],"considering":[239],"not":[240],"only":[241],"also":[246],"costs.":[249]},"counts_by_year":[],"updated_date":"2025-12-30T23:08:21.542490","created_date":"2025-10-10T00:00:00"}
