{"id":"https://openalex.org/W2904358772","doi":"https://doi.org/10.1109/access.2018.2884913","title":"DeepMEC: Mobile Edge Caching Using Deep Learning","display_name":"DeepMEC: Mobile Edge Caching Using Deep Learning","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2904358772","doi":"https://doi.org/10.1109/access.2018.2884913","mag":"2904358772"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2884913","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2884913","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2884913","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066200890","display_name":"Kyi Thar","orcid":"https://orcid.org/0000-0001-9390-6511"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyi Thar","raw_affiliation_strings":["Department of Computer Science and Engineering, Kyung Hee University, Yongin, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9390-6511","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Kyung Hee University, Yongin, South Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027558961","display_name":"Nguyen H. Tran","orcid":"https://orcid.org/0000-0001-7323-9213"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nguyen H. Tran","raw_affiliation_strings":["School of Computer Science, The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021969424","display_name":"Thant Zin Oo","orcid":"https://orcid.org/0000-0001-7644-2866"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Thant Zin Oo","raw_affiliation_strings":["Department of Computer Science and Engineering, Kyung Hee University, Yongin, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Kyung Hee University, Yongin, South Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034052371","display_name":"Choong Seon Hong","orcid":"https://orcid.org/0000-0003-3484-7333"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Choong Seon Hong","raw_affiliation_strings":["Department of Computer Science and Engineering, Kyung Hee University, Yongin, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Kyung Hee University, Yongin, South Korea","institution_ids":["https://openalex.org/I35928602"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.5221,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.96956324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"78260","last_page":"78275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":1.0,"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/T11478","display_name":"Caching and Content Delivery","score":1.0,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9419000148773193,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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/computer-science","display_name":"Computer science","score":0.8910051584243774},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.7176824808120728},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.6009085178375244},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5858075618743896},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5823989510536194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49138107895851135},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.47849979996681213},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.46203094720840454},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.45593777298927307},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.451748788356781},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4369978904724121},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4328814744949341},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4313439428806305},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4161606729030609},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3105906844139099},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.135297954082489}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8910051584243774},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.7176824808120728},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.6009085178375244},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5858075618743896},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5823989510536194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49138107895851135},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.47849979996681213},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.46203094720840454},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.45593777298927307},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.451748788356781},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4369978904724121},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4328814744949341},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4313439428806305},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4161606729030609},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3105906844139099},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.135297954082489},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2884913","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2884913","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a82ea20c2c9f43d8a51954f778ab1ff5","is_oa":true,"landing_page_url":"https://doaj.org/article/a82ea20c2c9f43d8a51954f778ab1ff5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 78260-78275 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2884913","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2884913","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1489537150","https://openalex.org/W1498436455","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1991607248","https://openalex.org/W2051773775","https://openalex.org/W2054237513","https://openalex.org/W2064675550","https://openalex.org/W2083637157","https://openalex.org/W2113952909","https://openalex.org/W2115519224","https://openalex.org/W2127652281","https://openalex.org/W2149706766","https://openalex.org/W2163598150","https://openalex.org/W2163605009","https://openalex.org/W2327853039","https://openalex.org/W2415391790","https://openalex.org/W2420559854","https://openalex.org/W2491602136","https://openalex.org/W2517672267","https://openalex.org/W2519564973","https://openalex.org/W2523246573","https://openalex.org/W2545900194","https://openalex.org/W2564103961","https://openalex.org/W2575485168","https://openalex.org/W2606089314","https://openalex.org/W2767547957","https://openalex.org/W2771556079","https://openalex.org/W2772149718","https://openalex.org/W2805358920","https://openalex.org/W2833256931","https://openalex.org/W2949117887","https://openalex.org/W2949704782","https://openalex.org/W2962850461","https://openalex.org/W2963008907","https://openalex.org/W2964121744","https://openalex.org/W3125952634","https://openalex.org/W4210984920","https://openalex.org/W4229602251","https://openalex.org/W4236137412","https://openalex.org/W4236706032","https://openalex.org/W6684191040","https://openalex.org/W6746178111"],"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":{"Caching":[0],"popular":[1,121],"contents":[2,35,39,83,122,148,160],"at":[3],"edge":[4],"nodes":[5],"such":[6],"as":[7],"base":[8,45,116],"stations":[9],"is":[10,25,73,112,186],"a":[11,189,195],"crucial":[12],"solution":[13],"for":[14],"improving":[15],"users'":[16],"quality":[17],"of":[18,34,82,138,147,182,194],"services":[19],"in":[20,43,52,68,96,176],"next-generation":[21],"networks.":[22],"However,":[23],"it":[24],"very":[26],"challenging":[27],"to":[28,75,84,101,114,118,222],"correctly":[29],"predict":[30,78],"the":[31,44,50,79,97,108,120,134,143,151,158,169,180,183,202,223],"future":[32,80,135,144],"popularity":[33,81,145,163],"and":[36,55,77,94,155,171,214],"decide":[37],"which":[38],"should":[40],"be":[41],"stored":[42],"station":[46,117],"cache.":[47],"Recently,":[48],"with":[49,161,188],"advances":[51],"big":[53],"data":[54,99],"high":[56,64,162],"computing":[57],"power,":[58],"deep":[59,71,89],"learning":[60,72,90],"models":[61,91,167],"have":[62],"achieved":[63],"prediction":[65,166],"accuracy.":[66],"Hence,":[67],"this":[69,177],"paper,":[70],"used":[74],"learn":[76],"support":[85],"cache":[86,105,110,196],"decision.":[87,106],"First,":[88],"are":[92,174],"trained":[93],"utilized":[95],"cloud":[98],"center":[100],"make":[102],"an":[103],"efficient":[104],"Then,":[107],"final":[109],"decision":[111],"sent":[113],"each":[115,139],"store":[119],"proactively.":[123],"The":[124,165],"proposed":[125,203],"caching":[126,157,184],"scheme":[127,204,211,218],"involves":[128],"three":[129],"distinct":[130],"parts:":[131],"1)":[132],"predicting":[133,142],"class":[136,153],"label":[137],"content;":[140],"2)":[141],"score":[146],"based":[149],"on":[150],"predicted":[152,159],"label;":[154],"3)":[156],"scores.":[164],"using":[168],"Keras":[170],"Tensorflow":[172],"libraries":[173],"implemented":[175],"paper.":[178],"Finally,":[179],"performance":[181],"schemes":[185],"tested":[187],"Python-based":[190],"simulator.":[191],"In":[192],"terms":[193],"hit,":[197],"simulation":[198],"results":[199],"show":[200],"that":[201],"outperforms":[205,212,219],"38%,":[206],"convolutional":[207,215],"recurrent":[208],"neural":[209,216],"network-based":[210,217],"33%,":[213],"25%":[220],"compared":[221],"baseline":[224],"scheme.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}