{"id":"https://openalex.org/W4312271112","doi":"https://doi.org/10.1109/case49997.2022.9926628","title":"Deep Reinforcement Learning-based Dynamic Bandwidth Allocation in Weighted Fair Queues of Routers","display_name":"Deep Reinforcement Learning-based Dynamic Bandwidth Allocation in Weighted Fair Queues of Routers","publication_year":2022,"publication_date":"2022-08-20","ids":{"openalex":"https://openalex.org/W4312271112","doi":"https://doi.org/10.1109/case49997.2022.9926628"},"language":"en","primary_location":{"id":"doi:10.1109/case49997.2022.9926628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case49997.2022.9926628","pdf_url":null,"source":{"id":"https://openalex.org/S4363607892","display_name":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","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":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","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/A5109953585","display_name":"Jinyan Pan","orcid":"https://orcid.org/0000-0003-0989-5157"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinyan Pan","raw_affiliation_strings":["Sun Yat-Sen University,School of Business,Guangzhou,P. R. China,510275"],"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University,School of Business,Guangzhou,P. R. China,510275","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389298","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-9597-497X"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Guangzhou University,School of Management,Guangzhou,P. R. China,510006"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Management,Guangzhou,P. R. China,510006","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100769821","display_name":"Haoran Wu","orcid":"https://orcid.org/0000-0001-5822-8698"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Wu","raw_affiliation_strings":["Sun Yat-Sen University,School of Business,Guangzhou,P. R. China,510275"],"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University,School of Business,Guangzhou,P. R. China,510275","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062468447","display_name":"Xi Peng","orcid":"https://orcid.org/0000-0002-8912-3351"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Peng","raw_affiliation_strings":["Huawei Technologies Co. Ltd.,Theory Lab, Hong Kong Research Center,Hong Kong,China","Theory Lab, Hong Kong Research Center, Huawei Technologies Co. Ltd., Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd.,Theory Lab, Hong Kong Research Center,Hong Kong,China","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"Theory Lab, Hong Kong Research Center, Huawei Technologies Co. Ltd., Hong Kong, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445622","display_name":"Xia Li","orcid":"https://orcid.org/0000-0003-3050-8529"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Xia","raw_affiliation_strings":["Sun Yat-Sen University,School of Business,Guangzhou,P. R. China,510275"],"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University,School of Business,Guangzhou,P. R. China,510275","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109953585"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":1.2971,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.79032258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1580","last_page":"1587"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10138","display_name":"Network Traffic and Congestion Control","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10138","display_name":"Network Traffic and Congestion Control","score":0.9997000098228455,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.9961000084877014,"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/T11409","display_name":"Advanced Wireless Network Optimization","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/weighted-fair-queueing","display_name":"Weighted fair queueing","score":0.9209809303283691},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.828988790512085},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6292123198509216},{"id":"https://openalex.org/keywords/queueing-theory","display_name":"Queueing theory","score":0.6094446778297424},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.6043633222579956},{"id":"https://openalex.org/keywords/bandwidth-allocation","display_name":"Bandwidth allocation","score":0.592437744140625},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.5502033233642578},{"id":"https://openalex.org/keywords/dynamic-bandwidth-allocation","display_name":"Dynamic bandwidth allocation","score":0.5309495329856873},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.5220189690589905},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.4947046935558319},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.45416268706321716},{"id":"https://openalex.org/keywords/random-early-detection","display_name":"Random early detection","score":0.4390646815299988},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.39556756615638733},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3764946460723877},{"id":"https://openalex.org/keywords/network-congestion","display_name":"Network congestion","score":0.3161999583244324},{"id":"https://openalex.org/keywords/active-queue-management","display_name":"Active queue management","score":0.23712453246116638},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.14548665285110474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12300249934196472}],"concepts":[{"id":"https://openalex.org/C102486512","wikidata":"https://www.wikidata.org/wiki/Q457762","display_name":"Weighted fair queueing","level":3,"score":0.9209809303283691},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.828988790512085},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6292123198509216},{"id":"https://openalex.org/C22684755","wikidata":"https://www.wikidata.org/wiki/Q847526","display_name":"Queueing theory","level":2,"score":0.6094446778297424},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.6043633222579956},{"id":"https://openalex.org/C200157131","wikidata":"https://www.wikidata.org/wiki/Q4854763","display_name":"Bandwidth allocation","level":3,"score":0.592437744140625},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.5502033233642578},{"id":"https://openalex.org/C145062175","wikidata":"https://www.wikidata.org/wiki/Q5318947","display_name":"Dynamic bandwidth allocation","level":3,"score":0.5309495329856873},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.5220189690589905},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.4947046935558319},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.45416268706321716},{"id":"https://openalex.org/C161965511","wikidata":"https://www.wikidata.org/wiki/Q560448","display_name":"Random early detection","level":5,"score":0.4390646815299988},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.39556756615638733},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3764946460723877},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.3161999583244324},{"id":"https://openalex.org/C34793927","wikidata":"https://www.wikidata.org/wiki/Q583367","display_name":"Active queue management","level":4,"score":0.23712453246116638},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.14548665285110474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12300249934196472},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case49997.2022.9926628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case49997.2022.9926628","pdf_url":null,"source":{"id":"https://openalex.org/S4363607892","display_name":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","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":"2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3013694835","https://openalex.org/W1884496646","https://openalex.org/W2351195593","https://openalex.org/W2379632558","https://openalex.org/W4229953098","https://openalex.org/W4224240262","https://openalex.org/W1515539439","https://openalex.org/W2057490875","https://openalex.org/W2318817008","https://openalex.org/W2366086320"],"abstract_inverted_index":{"Motivated":[0],"by":[1,97],"a":[2,22,53,86,94,144,153,161,182],"real":[3,133,169,185],"problem":[4],"of":[5,12,49,67,74,171,184],"service":[6],"mechanism":[7],"in":[8,21,168],"the":[9,17,56,71,101,114,121,174],"output":[10],"port":[11],"routers,":[13,172],"this":[14],"paper":[15],"studies":[16],"dynamic":[18,60],"bandwidth":[19,61,95,107],"allocation":[20],"G/G/1/K":[23],"parallel":[24],"queueing":[25,30],"system,":[26],"where":[27,173],"weighted":[28],"fair":[29],"(WFQ)":[31],"scheduling":[32],"discipline":[33],"is":[34,77,160,190],"applied":[35],"to":[36,92,113,164],"support":[37],"differentiated":[38],"services":[39],"for":[40,59],"different":[41],"packet":[42,149],"queues.":[43],"The":[44,103],"bursty":[45],"and":[46,80,129,148,181],"complicated":[47],"characteristics":[48],"Internet":[50,75],"traffic":[51,68,76,134,186],"pose":[52],"challenge":[54],"on":[55],"analytic":[57],"solution":[58],"allocation,":[62],"which":[63],"requires":[64],"distributional":[65,72],"information":[66,73],"patterns.":[69],"Since":[70],"always":[78],"unavailable":[79],"varied":[81],"with":[82,100,123],"time,":[83],"we":[84],"propose":[85],"deep":[87],"reinforcement":[88],"learning":[89],"(DRL)":[90],"framework":[91],"train":[93,120],"controller":[96,104,122],"adaptively":[98],"interacting":[99],"environment.":[102],"dynamically":[105],"allocates":[106],"weights":[108],"among":[109],"multiple":[110],"queues":[111,180],"according":[112],"instant":[115],"queue":[116],"lengths":[117],"observed.":[118],"We":[119],"two":[124],"advanced":[125],"DRL":[126],"algorithms,":[127],"DDPG":[128],"SAC,":[130],"respectively.":[131],"With":[132],"data,":[135],"experiment":[136],"results":[137],"show":[138],"that":[139],"our":[140],"trained":[141],"controllers":[142],"achieve":[143],"lower":[145],"average":[146],"delay":[147],"loss":[150],"rate":[151],"than":[152],"rule-based":[154],"policy.":[155],"Our":[156],"proposed":[157],"WFQ-DRL":[158],"algorithm":[159],"first":[162],"attempt":[163],"apply":[165],"RL":[166],"algorithms":[167],"scenarios":[170],"system":[175],"has":[176],"eight":[177],"or":[178],"more":[179],"diversity":[183],"without":[187],"Poisson":[188],"assumption":[189],"applicable.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
