{"id":"https://openalex.org/W3136338303","doi":"https://doi.org/10.1109/tvt.2021.3068255","title":"Deep Reinforcement Learning Based Resource Management for DNN Inference in Industrial IoT","display_name":"Deep Reinforcement Learning Based Resource Management for DNN Inference in Industrial IoT","publication_year":2021,"publication_date":"2021-03-23","ids":{"openalex":"https://openalex.org/W3136338303","doi":"https://doi.org/10.1109/tvt.2021.3068255","mag":"3136338303"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2021.3068255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2021.3068255","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","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/A5101707934","display_name":"Weiting Zhang","orcid":"https://orcid.org/0000-0002-7473-2234"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiting Zhang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7473-2234","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071654735","display_name":"Dong Yang","orcid":"https://orcid.org/0000-0003-3402-3668"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Yang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3402-3668","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102864216","display_name":"Haixia Peng","orcid":"https://orcid.org/0000-0001-7206-4706"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Haixia Peng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7206-4706","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074854979","display_name":"Wen Wu","orcid":"https://orcid.org/0000-0002-0458-1282"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wen Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0002-0458-1282","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036159136","display_name":"Wei Quan","orcid":"https://orcid.org/0000-0001-7454-0905"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Quan","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7454-0905","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091713195","display_name":"Hongke Zhang","orcid":"https://orcid.org/0000-0001-8906-813X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongke Zhang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8906-813X","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100773343","display_name":"Xuemin Shen","orcid":"https://orcid.org/0000-0002-4140-287X"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xuemin Shen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4140-287X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":14.1572,"has_fulltext":false,"cited_by_count":147,"citation_normalized_percentile":{"value":0.99319286,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"70","issue":"8","first_page":"7605","last_page":"7618"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9998000264167786,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9998000264167786,"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/T13553","display_name":"Age of Information Optimization","score":0.9943000078201294,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9932000041007996,"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/inference","display_name":"Inference","score":0.7829055786132812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7276113629341125},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6389569044113159},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6194919347763062},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.605054497718811},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5639950633049011},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.5588882565498352},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46914616227149963},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.46424970030784607},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46162962913513184},{"id":"https://openalex.org/keywords/integer-programming","display_name":"Integer programming","score":0.46147844195365906},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4603646993637085},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4538083076477051},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.4386792778968811},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4162452816963196},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3846096396446228},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.19289839267730713},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.14217805862426758},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10453206300735474}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7829055786132812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7276113629341125},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6389569044113159},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6194919347763062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.605054497718811},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5639950633049011},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.5588882565498352},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46914616227149963},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.46424970030784607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46162962913513184},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.46147844195365906},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4603646993637085},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4538083076477051},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.4386792778968811},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4162452816963196},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3846096396446228},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.19289839267730713},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.14217805862426758},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10453206300735474},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2021.3068255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2021.3068255","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G7293739128","display_name":null,"funder_award_id":"2018YFB1702000","funder_id":"https://openalex.org/F4320336026","funder_display_name":"National Key Research and Development Program of China Stem Cell and Translational Research"},{"id":"https://openalex.org/G7892434890","display_name":null,"funder_award_id":"2018YFE0206800","funder_id":"https://openalex.org/F4320336026","funder_display_name":"National Key Research and Development Program of China Stem Cell and Translational Research"},{"id":"https://openalex.org/G8260795663","display_name":"\u9762\u5411\u63a7\u5236\u548c\u5b89\u5168\u5e94\u7528\u7684\u5de5\u4e1a\u65e0\u7ebf\u4f20\u611f\u5668\u7f51\u7edc\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61771040","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"},{"id":"https://openalex.org/F4320336026","display_name":"National Key Research and Development Program of China Stem Cell and Translational Research","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2101972630","https://openalex.org/W2604319603","https://openalex.org/W2615459164","https://openalex.org/W2761862361","https://openalex.org/W2771250869","https://openalex.org/W2787938642","https://openalex.org/W2811266402","https://openalex.org/W2898035736","https://openalex.org/W2900376989","https://openalex.org/W2902952649","https://openalex.org/W2913729121","https://openalex.org/W2920054549","https://openalex.org/W2924948991","https://openalex.org/W2942889782","https://openalex.org/W2944364052","https://openalex.org/W2947710575","https://openalex.org/W2963864421","https://openalex.org/W2963923407","https://openalex.org/W2964233199","https://openalex.org/W2968424451","https://openalex.org/W2968782695","https://openalex.org/W2974178109","https://openalex.org/W2976382054","https://openalex.org/W2979680647","https://openalex.org/W2979987893","https://openalex.org/W2980856918","https://openalex.org/W2981114133","https://openalex.org/W2989596860","https://openalex.org/W2990994567","https://openalex.org/W2999562137","https://openalex.org/W3010301175","https://openalex.org/W3011091971","https://openalex.org/W3016146955","https://openalex.org/W3021066175","https://openalex.org/W3045860335","https://openalex.org/W3047371394","https://openalex.org/W3059280052","https://openalex.org/W3092302056","https://openalex.org/W3110381504","https://openalex.org/W3125705797","https://openalex.org/W6631190155","https://openalex.org/W6684921986","https://openalex.org/W6748839928","https://openalex.org/W6789452587"],"related_works":["https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W4313463218","https://openalex.org/W3106131444","https://openalex.org/W3216099748","https://openalex.org/W4205963435","https://openalex.org/W4312996489","https://openalex.org/W3214037210"],"abstract_inverted_index":{"Performing":[0],"deep":[1,135,181],"neural":[2],"network":[3,11],"(DNN)":[4],"inference":[5,43,91,100,174],"in":[6,31,40,60],"real":[7],"time":[8],"requires":[9],"excessive":[10],"resources,":[12,170],"which":[13,41,128],"poses":[14],"a":[15,80,124,134],"big":[16],"challenge":[17],"to":[18,71,87,103,111,144,155],"the":[19,29,42,54,61,67,89,95,104,113,120,158,164,180],"resource-limited":[20],"industrial":[21],"Internet":[22],"of":[23,99],"things":[24],"(IIoT)":[25],"networks.":[26],"To":[27,75],"address":[28],"challenge,":[30],"this":[32],"paper,":[33],"we":[34,118],"introduce":[35],"an":[36],"end-edge-cloud":[37],"orchestration":[38],"architecture,":[39],"task":[44],"assignment":[45],"and":[46,58,69,168,171],"DNN":[47,55,73,78],"model":[48],"placement":[49],"are":[50,63,153],"flexibly":[51],"coordinated.":[52],"Specifically,":[53],"models,":[56],"trained":[57],"pre-stored":[59],"cloud,":[62],"properly":[64],"placed":[65],"at":[66],"end":[68],"edge":[70],"perform":[72],"inference.":[74],"achieve":[76],"efficient":[77],"inference,":[79],"multi-dimensional":[81],"resource":[82,139,148],"management":[83,140],"problem":[84,115,122],"is":[85,109,142],"formulated":[86,114,121],"maximize":[88],"average":[90,173],"accuracy":[92,175],"while":[93],"satisfying":[94],"strict":[96],"delay":[97],"requirements":[98],"tasks.":[101],"Due":[102],"mix-integer":[105],"decision":[106,126],"variables,":[107],"it":[108],"difficult":[110],"solve":[112],"directly.":[116],"Thus,":[117],"transform":[119],"into":[123],"Markov":[125],"process":[127],"can":[129,161],"be":[130],"solved":[131],"efficiently.":[132],"Furthermore,":[133],"reinforcement":[136],"learning":[137],"based":[138],"scheme":[141,160],"proposed":[143,159],"make":[145],"real-time":[146],"optimal":[147],"allocation":[149],"decisions.":[150],"Simulation":[151],"results":[152],"provided":[154],"demonstrate":[156],"that":[157],"efficiently":[162],"allocate":[163],"available":[165],"spectrum,":[166],"caching,":[167],"computing":[169],"improve":[172],"by":[176],"31.4$\\%$":[177],"compared":[178],"with":[179],"deterministic":[182],"policy":[183],"gradient":[184],"benchmark.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":43},{"year":2022,"cited_by_count":34},{"year":2021,"cited_by_count":5}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}