{"id":"https://openalex.org/W4300850679","doi":"https://doi.org/10.1109/icc45855.2022.9838521","title":"Communication Traffic Prediction with Continual Knowledge Distillation","display_name":"Communication Traffic Prediction with Continual Knowledge Distillation","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4300850679","doi":"https://doi.org/10.1109/icc45855.2022.9838521"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9838521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838521","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-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/A5100455129","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-1230-4007"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hang Li","raw_affiliation_strings":["Samsung Electronics,Canada","Samsung Electronics, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Canada","institution_ids":[]},{"raw_affiliation_string":"Samsung Electronics, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083959011","display_name":"Ju Wang","orcid":"https://orcid.org/0000-0001-8026-9787"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ju Wang","raw_affiliation_strings":["Samsung Electronics,Canada","Samsung Electronics, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Canada","institution_ids":[]},{"raw_affiliation_string":"Samsung Electronics, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038612451","display_name":"Chengming Hu","orcid":"https://orcid.org/0000-0002-1099-0736"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chengming Hu","raw_affiliation_strings":["Samsung Electronics,Canada","Samsung Electronics, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Canada","institution_ids":[]},{"raw_affiliation_string":"Samsung Electronics, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329832","display_name":"Xi Chen","orcid":"https://orcid.org/0000-0001-5395-4295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xi Chen","raw_affiliation_strings":["Samsung Electronics,Canada","Samsung Electronics, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Canada","institution_ids":[]},{"raw_affiliation_string":"Samsung Electronics, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100759705","display_name":"Xue Liu","orcid":"https://orcid.org/0000-0002-5159-8503"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue Liu","raw_affiliation_strings":["Samsung Electronics,Canada","Samsung Electronics, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Canada","institution_ids":[]},{"raw_affiliation_string":"Samsung Electronics, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028155175","display_name":"Seowoo Jang","orcid":"https://orcid.org/0000-0001-8044-3730"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seowoo Jang","raw_affiliation_strings":["Samsung Electronics,Korea (South)","Samsung Electronics, Korea (South)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Korea (South)","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Electronics, Korea (South)","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075441381","display_name":"Gregory Dudek","orcid":"https://orcid.org/0000-0001-5040-4925"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gregory Dudek","raw_affiliation_strings":["Samsung Electronics,Canada","Samsung Electronics, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Canada","institution_ids":[]},{"raw_affiliation_string":"Samsung Electronics, Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6735,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.84186992,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5481","last_page":"5486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9959999918937683,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.7552663087844849},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6135590076446533},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5679590702056885},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5126151442527771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49045321345329285},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.46626147627830505},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4461539387702942},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4271481931209564},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.41512367129325867}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7552663087844849},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6135590076446533},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5679590702056885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5126151442527771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49045321345329285},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.46626147627830505},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4461539387702942},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4271481931209564},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.41512367129325867},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9838521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838521","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1598519330","https://openalex.org/W1690739335","https://openalex.org/W1821462560","https://openalex.org/W2018798792","https://openalex.org/W2051773775","https://openalex.org/W2077537883","https://openalex.org/W2113213522","https://openalex.org/W2152364540","https://openalex.org/W2166277028","https://openalex.org/W2561238782","https://openalex.org/W2612759037","https://openalex.org/W2739879705","https://openalex.org/W2762605243","https://openalex.org/W2804250895","https://openalex.org/W2807536558","https://openalex.org/W2892880745","https://openalex.org/W2903500163","https://openalex.org/W2921319277","https://openalex.org/W2954901156","https://openalex.org/W2963035276","https://openalex.org/W2963389592","https://openalex.org/W2982572724","https://openalex.org/W6631190155","https://openalex.org/W6635815882","https://openalex.org/W6637551013","https://openalex.org/W6638523607","https://openalex.org/W6765492279","https://openalex.org/W6842607031"],"related_works":["https://openalex.org/W1629725936","https://openalex.org/W3160244858","https://openalex.org/W4312949351","https://openalex.org/W4221031036","https://openalex.org/W2479199381","https://openalex.org/W4223943233","https://openalex.org/W4320483443","https://openalex.org/W2347258627","https://openalex.org/W4366376591","https://openalex.org/W4211071659"],"abstract_inverted_index":{"Accurate":[0],"traffic":[1,60,122,128,139,207],"volume":[2],"estimation":[3],"and":[4,17,62,93,157],"prediction":[5,47,72,103,116,156,171,208,217],"are":[6],"essential":[7],"for":[8,178],"advanced":[9],"communication":[10,59],"network":[11,151],"functions,":[12],"such":[13],"as":[14,141,143],"automatic":[15],"operations":[16],"predictive":[18],"resource":[19],"allocation.":[20],"Although":[21],"machine":[22],"learning":[23],"(ML)-based":[24],"approaches":[25,34],"achieve":[26],"great":[27],"success":[28],"in":[29,50,66],"accomplishing":[30],"this":[31,106],"goal,":[32],"existing":[33],"suffer":[35],"from":[36,99,167],"two":[37],"drawbacks":[38],"that":[39,113,196],"limit":[40],"their":[41],"real-world":[42,193],"applications.":[43],"First,":[44],"the":[45,51,58,67,89,115,119,131,135,162,165,179,197,201,215],"ML-based":[46],"models":[48],"developed":[49],"past":[52],"might":[53],"be":[54],"obsolete":[55],"now,":[56],"since":[57],"patterns":[61],"volumes":[63],"keep":[64],"changing":[65,121],"real":[68],"world,":[69],"leading":[70],"to":[71,88,118,173,211,214],"errors.":[73],"Second,":[74],"most":[75],"Base":[76],"Stations":[77],"(BSs)":[78],"can":[79],"only":[80,124],"save":[81],"a":[82,110,125,147,155,158,174,184,192],"small":[83],"amount":[84],"of":[85,137,206],"data":[86,140],"due":[87],"limited":[90],"storage":[91,95],"capacity":[92],"high":[94],"costs,":[96],"which":[97,153],"prevents":[98],"training":[100],"an":[101,168],"accurate":[102],"model.":[104],"In":[105],"paper,":[107],"we":[108],"propose":[109],"novel":[111],"framework":[112,132,163,199],"adapts":[114],"model":[117,172,177,180],"constantly":[120],"with":[123],"few":[126],"current":[127],"data.":[129],"Specifically,":[130],"first":[133],"learns":[134],"knowledge":[136,166,187],"historical":[138],"much":[142],"possible":[144],"by":[145,182,209],"using":[146,183],"proposed":[148,185,198],"two-branch":[149],"neural":[150],"design,":[152],"includes":[154],"reconstruction":[159],"module.":[160],"Then,":[161],"transfers":[164],"old":[169],"(past)":[170],"new":[175],"(current)":[176],"update":[181],"continual":[186],"distillation":[188],"technique.":[189],"Evaluations":[190],"on":[191],"dataset":[194],"show":[195],"reduces":[200],"Mean":[202],"Absolute":[203],"Error":[204],"(MAE)":[205],"up":[210],"9.62%":[212],"compared":[213],"state-of-the-art":[216],"methods.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}