{"id":"https://openalex.org/W4414140589","doi":"https://doi.org/10.1109/icmew68306.2025.11152098","title":"AI-Assisted Edge Server Selection in 5G for Low-Latency Multimedia Applications","display_name":"AI-Assisted Edge Server Selection in 5G for Low-Latency Multimedia Applications","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4414140589","doi":"https://doi.org/10.1109/icmew68306.2025.11152098"},"language":"en","primary_location":{"id":"doi:10.1109/icmew68306.2025.11152098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew68306.2025.11152098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","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/A5101596596","display_name":"A. Hassanein","orcid":"https://orcid.org/0000-0003-1488-2000"},"institutions":[{"id":"https://openalex.org/I9374425","display_name":"Ottawa University","ror":"https://ror.org/04jscf286","country_code":"US","type":"education","lineage":["https://openalex.org/I9374425"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ahmed Hassanein","raw_affiliation_strings":["University of Ottawa,Discover Lab, School of EECS,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"University of Ottawa,Discover Lab, School of EECS,Ottawa,Canada","institution_ids":["https://openalex.org/I9374425"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036640771","display_name":"Mahmoud Reza Hashemi","orcid":"https://orcid.org/0000-0002-3518-9195"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mahmoud Reza Hashemi","raw_affiliation_strings":["University of Tehran,School of Electrical and Computer Engineering, College of Engineering,Tehran,Iran"],"affiliations":[{"raw_affiliation_string":"University of Tehran,School of Electrical and Computer Engineering, College of Engineering,Tehran,Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044422170","display_name":"Shervin Shirmohammadi","orcid":"https://orcid.org/0000-0002-3973-4445"},"institutions":[{"id":"https://openalex.org/I9374425","display_name":"Ottawa University","ror":"https://ror.org/04jscf286","country_code":"US","type":"education","lineage":["https://openalex.org/I9374425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shervin Shirmohammadi","raw_affiliation_strings":["University of Ottawa,Discover Lab, School of EECS,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"University of Ottawa,Discover Lab, School of EECS,Ottawa,Canada","institution_ids":["https://openalex.org/I9374425"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101596596"],"corresponding_institution_ids":["https://openalex.org/I9374425"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25174145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9965000152587891,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.6890000104904175},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5932999849319458},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5310999751091003},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.51419997215271},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.43369999527931213},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4271000027656555},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.42419999837875366},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4146000146865845},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.3986000120639801}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8238000273704529},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.6890000104904175},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5932999849319458},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.5151000022888184},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.51419997215271},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.43369999527931213},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4271000027656555},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.42419999837875366},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.42239999771118164},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4146000146865845},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39649999141693115},{"id":"https://openalex.org/C2776855496","wikidata":"https://www.wikidata.org/wiki/Q177518","display_name":"IPTV","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.33649998903274536},{"id":"https://openalex.org/C134535813","wikidata":"https://www.wikidata.org/wiki/Q1888734","display_name":"Transcoding","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.3239000141620636},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3012000024318695},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28060001134872437},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.27959999442100525},{"id":"https://openalex.org/C164554305","wikidata":"https://www.wikidata.org/wiki/Q71550","display_name":"Application server","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.25839999318122864},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2533000111579895},{"id":"https://openalex.org/C2775973920","wikidata":"https://www.wikidata.org/wiki/Q3252726","display_name":"Selection algorithm","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew68306.2025.11152098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew68306.2025.11152098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2739965732","https://openalex.org/W3013557734","https://openalex.org/W3017194848","https://openalex.org/W3034488271","https://openalex.org/W3120759960","https://openalex.org/W3132619898","https://openalex.org/W3188282212","https://openalex.org/W3193818225","https://openalex.org/W3209283715","https://openalex.org/W3215978122","https://openalex.org/W4220839771","https://openalex.org/W4225494949","https://openalex.org/W4225984761","https://openalex.org/W4241396323","https://openalex.org/W4307950832","https://openalex.org/W4312722077","https://openalex.org/W4367665491","https://openalex.org/W4384518428","https://openalex.org/W4385722530","https://openalex.org/W4386158785","https://openalex.org/W4390401795","https://openalex.org/W4401597675","https://openalex.org/W4408359431"],"related_works":["https://openalex.org/W4205762803","https://openalex.org/W2535856026","https://openalex.org/W2265065644","https://openalex.org/W3205411230","https://openalex.org/W4286899009","https://openalex.org/W9168048","https://openalex.org/W4300849822","https://openalex.org/W4376480820","https://openalex.org/W3155891479","https://openalex.org/W3029351463"],"abstract_inverted_index":{"Efficient":[0],"edge":[1],"server":[2,82],"selection":[3],"in":[4,38,131],"5G":[5,71,132],"networks":[6],"is":[7],"vital":[8],"for":[9,117,127],"supporting":[10],"low-latency":[11,39],"multimedia":[12],"applications":[13],"like":[14],"live":[15],"video":[16],"streaming":[17],"and":[18,55,81,115,133],"online":[19],"gaming.":[20],"This":[21,119],"paper":[22],"proposes":[23],"AI":[24],"approaches,":[25,29],"specially":[26],"deep":[27,125],"learning":[28,126],"to":[30,35,112],"dynamically":[31],"assign":[32],"user":[33,80],"requests":[34],"optimal":[36],"servers":[37],"scenarios,":[40],"utilizing":[41],"Deep":[42],"Neural":[43],"Networks":[44],"(DNN),":[45],"Long":[46],"Short-Term":[47],"Memory":[48],"(LSTM)":[49],"networks,":[50],"Gated":[51],"Recurrent":[52],"Units":[53],"(GRU)":[54],"various":[56],"Transformer":[57],"model":[58,88],"variations.":[59],"The":[60,105],"models":[61],"were":[62],"trained":[63],"on":[64],"a":[65],"custom":[66],"dataset":[67],"derived":[68],"from":[69],"real-world":[70],"traffic,":[72],"incorporating":[73],"features":[74],"such":[75],"as":[76],"latency,":[77],"packet":[78],"lengths,":[79],"geolocation.":[83],"Among":[84],"these,":[85],"the":[86,90,122],"GRU":[87],"achieved":[89],"highest":[91],"accuracy":[92],"of":[93,124],"94.72":[94],"%,":[95],"outperforming":[96],"other":[97],"models,":[98],"while":[99],"maintaing":[100],"relatively":[101],"low":[102],"inference":[103],"time.":[104],"conducted":[106],"confusion":[107],"matrix":[108],"analysis":[109],"highlights":[110],"adaptability":[111],"network":[113],"conditions":[114],"areas":[116],"improvement.":[118],"study":[120],"demonstrates":[121],"promise":[123],"intelligent":[128],"resource":[129],"allocation":[130],"future":[134],"6G":[135],"networks.":[136]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}