{"id":"https://openalex.org/W2999502953","doi":"https://doi.org/10.1109/tvt.2020.2965796","title":"A New Block-Based Reinforcement Learning Approach for Distributed Resource Allocation in Clustered IoT Networks","display_name":"A New Block-Based Reinforcement Learning Approach for Distributed Resource Allocation in Clustered IoT Networks","publication_year":2020,"publication_date":"2020-01-10","ids":{"openalex":"https://openalex.org/W2999502953","doi":"https://doi.org/10.1109/tvt.2020.2965796","mag":"2999502953"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2020.2965796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2965796","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/A5044266495","display_name":"Fatima Hussain","orcid":"https://orcid.org/0000-0002-6306-9772"},"institutions":[{"id":"https://openalex.org/I125133608","display_name":"Royal Bank of Canada","ror":"https://ror.org/03hgnwx26","country_code":"CA","type":"other","lineage":["https://openalex.org/I125133608"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Fatima Hussain","raw_affiliation_strings":["Royal Bank of Canada, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Royal Bank of Canada, Toronto, Canada","institution_ids":["https://openalex.org/I125133608"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090705977","display_name":"Rasheed Hussain","orcid":"https://orcid.org/0000-0002-3771-7537"},"institutions":[{"id":"https://openalex.org/I4210116741","display_name":"Innopolis University","ror":"https://ror.org/02b7jh107","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210116741"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Rasheed Hussain","raw_affiliation_strings":["Institute of Information Security and Cyber-Physical Systems, Innopolis University, Innopolis, Russia"],"affiliations":[{"raw_affiliation_string":"Institute of Information Security and Cyber-Physical Systems, Innopolis University, Innopolis, Russia","institution_ids":["https://openalex.org/I4210116741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074463174","display_name":"Alagan Anpalagan","orcid":"https://orcid.org/0000-0002-6646-6052"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alagan Anpalagan","raw_affiliation_strings":["WINCORE Lab, Department of Computer Science, Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"WINCORE Lab, Department of Computer Science, Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060341203","display_name":"Abderrahim Benslimane","orcid":"https://orcid.org/0000-0001-9307-6132"},"institutions":[{"id":"https://openalex.org/I198415970","display_name":"Universit\u00e9 d'Avignon et des Pays de Vaucluse","ror":"https://ror.org/00mfpxb84","country_code":"FR","type":"education","lineage":["https://openalex.org/I198415970"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Abderrahim Benslimane","raw_affiliation_strings":["University of Avigon, Avignon, France"],"affiliations":[{"raw_affiliation_string":"University of Avigon, Avignon, France","institution_ids":["https://openalex.org/I198415970"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044266495"],"corresponding_institution_ids":["https://openalex.org/I125133608"],"apc_list":null,"apc_paid":null,"fwci":2.8002,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.9087692,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"69","issue":"3","first_page":"2891","last_page":"2904"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12079","display_name":"IoT Networks and Protocols","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12079","display_name":"IoT Networks and Protocols","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9993000030517578,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.7801197171211243},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.6454931497573853},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.6424565315246582},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6372644901275635},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5294722318649292},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5263432264328003},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.46964117884635925},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.44831281900405884},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.4324554204940796},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4226035475730896},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.38809293508529663},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16636592149734497},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.13262322545051575},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09294745326042175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7801197171211243},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6454931497573853},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.6424565315246582},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6372644901275635},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5294722318649292},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5263432264328003},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.46964117884635925},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.44831281900405884},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.4324554204940796},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4226035475730896},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.38809293508529663},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16636592149734497},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.13262322545051575},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09294745326042175},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tvt.2020.2965796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2965796","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"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/061eca7c-c8ba-4b2f-b67d-e2bde31b3d7f","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/061eca7c-c8ba-4b2f-b67d-e2bde31b3d7f","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","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":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hussain, F, Hussain, R, Anpalagan, A & Benslimane, A 2020, 'A New Block-Based Reinforcement Learning Approach for Distributed Resource Allocation in Clustered IoT Networks', IEEE Transactions on Vehicular Technology, vol. 69, no. 3, 8955961, pp. 2891-2904. https://doi.org/10.1109/TVT.2020.2965796","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1486723693","https://openalex.org/W1778608605","https://openalex.org/W1966552195","https://openalex.org/W1969061574","https://openalex.org/W1973055251","https://openalex.org/W2010876592","https://openalex.org/W2025356004","https://openalex.org/W2051376838","https://openalex.org/W2059000645","https://openalex.org/W2078385798","https://openalex.org/W2079234962","https://openalex.org/W2086826630","https://openalex.org/W2087838764","https://openalex.org/W2090085870","https://openalex.org/W2101124704","https://openalex.org/W2104602264","https://openalex.org/W2109401393","https://openalex.org/W2110767187","https://openalex.org/W2123879133","https://openalex.org/W2124364062","https://openalex.org/W2125890412","https://openalex.org/W2128569883","https://openalex.org/W2130711276","https://openalex.org/W2163623545","https://openalex.org/W2163905491","https://openalex.org/W2202997502","https://openalex.org/W2312668963","https://openalex.org/W2341653212","https://openalex.org/W2343382616","https://openalex.org/W2475894509","https://openalex.org/W2527914898","https://openalex.org/W2542461056","https://openalex.org/W2592124219","https://openalex.org/W2603166392","https://openalex.org/W2609731728","https://openalex.org/W2758296822","https://openalex.org/W2761694337","https://openalex.org/W2764311431","https://openalex.org/W2788005034","https://openalex.org/W2788017311","https://openalex.org/W2792005857","https://openalex.org/W2803418695","https://openalex.org/W2810871807","https://openalex.org/W2960189638","https://openalex.org/W2978245615","https://openalex.org/W3100857292","https://openalex.org/W4297789760","https://openalex.org/W6675811377","https://openalex.org/W6683851007","https://openalex.org/W6734096758","https://openalex.org/W6744749404","https://openalex.org/W6748239807"],"related_works":["https://openalex.org/W2923452570","https://openalex.org/W206598027","https://openalex.org/W2978610750","https://openalex.org/W2022931285","https://openalex.org/W1589966275","https://openalex.org/W2086872282","https://openalex.org/W2137789903","https://openalex.org/W1592324786","https://openalex.org/W2534160330","https://openalex.org/W2153007255"],"abstract_inverted_index":{"Resource":[0],"allocation":[1,56,80,107],"and":[2,19,41,66,84,91,97,146,174,188,191,228,235,258],"spectrum":[3],"management":[4,68],"are":[5,82,102,122],"two":[6],"major":[7],"challenges":[8],"in":[9,32,61,125,142,153,168,204],"the":[10,24,44,63,77,89,119,126,143,164,169,179,194,213,216,225,229,238,284],"massive":[11],"scale":[12],"deployment":[13],"of":[14,16,27,43,69,76,116,166,215,240],"Internet":[15],"Things":[17],"(IoT)":[18],"Machine-to-Machine":[20],"(M2M)":[21],"communication.":[22],"Furthermore,":[23],"large":[25,114],"number":[26,115],"devices":[28,117,145],"per":[29],"unit":[30],"area":[31],"IoT":[33,70,93,155,260],"networks":[34],"also":[35,109],"leads":[36],"to":[37,46,185,192,196,221,255,265],"congestion,":[38],"network":[39,261,274],"overload,":[40],"deterioration":[42],"Signal":[45,195],"Noise":[47],"Ratio":[48,198],"(SNR).":[49],"To":[50,72],"address":[51],"these":[52],"problems,":[53],"efficient":[54],"resource":[55,79,106],"play":[57],"a":[58,133,205,246,266],"pivotal":[59],"role":[60],"optimizing":[62],"throughput,":[64],"delay,":[65],"power":[67],"networks.":[71,94,156],"this":[73,129],"end,":[74],"most":[75],"existing":[78],"mechanisms":[81],"centralized":[83],"do":[85],"not":[86],"gracefully":[87],"support":[88],"heterogeneous":[90],"dynamic":[92],"Therefore,":[95],"distributed":[96,105,135,180,217,285],"Machine":[98,147],"Learning":[99],"(ML)-based":[100],"approaches":[101,121],"essential.":[103],"However,":[104],"techniques":[108],"have":[110],"scalability":[111],"problem":[112],"with":[113,249],"whereas":[118],"ML-based":[120],"currently":[123],"scarce":[124],"literature.":[127],"In":[128],"paper,":[130],"we":[131,211],"propose":[132,159],"new":[134],"block-based":[136],"Q-learning":[137],"algorithm":[138],"for":[139,163],"slot":[140,248,286],"scheduling":[141],"smart":[144],"Type":[148],"Communication":[149],"Devices":[150],"(MTCDs)":[151],"participating":[152],"clustered":[154],"We":[157],"furthermore,":[158],"various":[160],"reward":[161],"schemes":[162],"evolution":[165],"Q-values":[167],"proposed":[170,242],"scheme":[171],"and,":[172],"discuss":[173],"evaluate":[175],"their":[176],"effect":[177],"on":[178,224],"model.":[181],"Our":[182,232],"goal":[183],"is":[184,253,276],"avoid":[186],"inter-":[187],"intra-cluster":[189,271],"interference,":[190],"improve":[193],"Interference":[197],"(SIR)":[199],"by":[200],"employing":[201],"frequency":[202],"diversity":[203],"multi-channel":[206],"system.":[207],"Through":[208],"extensive":[209],"simulations,":[210],"analyze":[212],"effects":[214],"slot-assignment":[218],"(with":[219],"respect":[220],"varying":[222],"SIR)":[223],"convergence":[226,230,275],"rate":[227],"probability.":[231],"theoretical":[233],"analysis":[234],"simulations":[236],"validate":[237],"effectiveness":[239],"our":[241],"method":[243],"where,":[244],"(i)":[245],"suitable":[247],"acceptable":[250],"SIR":[251],"levels":[252],"allocated":[254],"each":[256,279],"MTCD,":[257],"(ii)":[259],"can":[262],"efficiently":[263],"converge":[264],"collision-free":[267],"transmission":[268],"causing":[269],"minimum":[270],"interference.":[272],"The":[273],"achieved":[277],"through":[278],"MTCD's":[280],"learning":[281],"ability":[282],"during":[283],"allocation.":[287]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
