{"id":"https://openalex.org/W2990920110","doi":"https://doi.org/10.1109/access.2019.2954546","title":"DMS: Dynamic Model Scaling for Quality-Aware Deep Learning Inference in Mobile and Embedded Devices","display_name":"DMS: Dynamic Model Scaling for Quality-Aware Deep Learning Inference in Mobile and Embedded Devices","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2990920110","doi":"https://doi.org/10.1109/access.2019.2954546","mag":"2990920110"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2954546","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2954546","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08907822.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://ieeexplore.ieee.org/ielx7/6287639/8600701/08907822.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103049674","display_name":"Woochul Kang","orcid":"https://orcid.org/0000-0002-4757-8999"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Woochul Kang","raw_affiliation_strings":["Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100644919","display_name":"Dae-Yeon Kim","orcid":"https://orcid.org/0000-0001-9396-480X"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daeyeon Kim","raw_affiliation_strings":["Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100354908","display_name":"Junyoung Park","orcid":"https://orcid.org/0000-0002-6248-2418"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junyoung Park","raw_affiliation_strings":["Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103049674"],"corresponding_institution_ids":["https://openalex.org/I146429904"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0216,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.81395715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"168048","last_page":"168059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9940999746322632,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8632361888885498},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7527934312820435},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6737325191497803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6462714672088623},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.628218948841095},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6040616035461426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5383201241493225},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.537975013256073},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.43938037753105164},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33605480194091797},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13549435138702393}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8632361888885498},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7527934312820435},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6737325191497803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6462714672088623},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.628218948841095},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6040616035461426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5383201241493225},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.537975013256073},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.43938037753105164},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33605480194091797},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13549435138702393},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2954546","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2954546","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08907822.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:57c106e5aea4419da51bdbd4112d77e8","is_oa":true,"landing_page_url":"https://doaj.org/article/57c106e5aea4419da51bdbd4112d77e8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 7, Pp 168048-168059 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2954546","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2954546","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08907822.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.5}],"awards":[{"id":"https://openalex.org/G2384678566","display_name":null,"funder_award_id":"NRF-2016R1D1A1B03934266","funder_id":"https://openalex.org/F4320311687","funder_display_name":"Ministry of Education"},{"id":"https://openalex.org/G3860156429","display_name":null,"funder_award_id":"NRF-2019R1F1A1060959","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G4244126222","display_name":null,"funder_award_id":"NRF-2016","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G5457564767","display_name":null,"funder_award_id":"NRF-2016R1D1A","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G5811536628","display_name":null,"funder_award_id":"NRF-2016R1D1A1B03934266","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G6309026452","display_name":null,"funder_award_id":"2016R1D1A1B03934266","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7685055460","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G8026418486","display_name":null,"funder_award_id":"2016R1D1A1B0393","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8596617356","display_name":null,"funder_award_id":"93426","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G982292920","display_name":null,"funder_award_id":"NRF-20","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2990920110.pdf","grobid_xml":"https://content.openalex.org/works/W2990920110.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W182691100","https://openalex.org/W1495021188","https://openalex.org/W1686810756","https://openalex.org/W1996901117","https://openalex.org/W2015244008","https://openalex.org/W2067523571","https://openalex.org/W2080663940","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2134807578","https://openalex.org/W2135099885","https://openalex.org/W2147800946","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2265166184","https://openalex.org/W2276892413","https://openalex.org/W2285660444","https://openalex.org/W2294543795","https://openalex.org/W2562731582","https://openalex.org/W2599379624","https://openalex.org/W2606722458","https://openalex.org/W2615131227","https://openalex.org/W2752037867","https://openalex.org/W2799026378","https://openalex.org/W2883839680","https://openalex.org/W2886851211","https://openalex.org/W2897268228","https://openalex.org/W2898170443","https://openalex.org/W2904990161","https://openalex.org/W2950014519","https://openalex.org/W2950248853","https://openalex.org/W2953384591","https://openalex.org/W2962677625","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963037989","https://openalex.org/W2963393494","https://openalex.org/W3118608800","https://openalex.org/W4236853429","https://openalex.org/W4297775537","https://openalex.org/W6637373629","https://openalex.org/W6649495467","https://openalex.org/W6677103964","https://openalex.org/W6677580257","https://openalex.org/W6684191040","https://openalex.org/W6684563725","https://openalex.org/W6713134421","https://openalex.org/W6726275242","https://openalex.org/W6735636592","https://openalex.org/W6737664043","https://openalex.org/W6743912273","https://openalex.org/W6745447533","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2373300491","https://openalex.org/W4375867731","https://openalex.org/W2395294869","https://openalex.org/W2378744544","https://openalex.org/W2594301978","https://openalex.org/W2379704676","https://openalex.org/W1998810860","https://openalex.org/W4206442282","https://openalex.org/W2384505857","https://openalex.org/W4390846322"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,34,80,89,140,152],"learning":[2,35,81,90,141,153],"has":[3],"brought":[4],"revolutions":[5],"to":[6,28,74,112],"many":[7],"mobile":[8],"and":[9,133,188],"embedded":[10],"systems":[11],"that":[12,69,116],"interact":[13],"with":[14,155,178],"the":[15,30,85,135,146,162],"physical":[16],"world":[17],"using":[18],"continuous":[19],"video":[20],"streams.":[21],"Although":[22],"there":[23],"have":[24,42],"been":[25],"significant":[26],"efforts":[27],"reduce":[29],"computational":[31],"overheads":[32],"of":[33,79,88,98,105,119,138,164],"inference":[36,91,190],"in":[37,49],"such":[38],"systems,":[39],"previous":[40],"approaches":[41],"focused":[43],"on":[44],"delivering":[45],"\u2018best-effort\u2019":[46],"performance,":[47],"resulting":[48],"unpredictable":[50,193],"performance":[51,191],"under":[52],"variable":[53],"environments.":[54],"In":[55,83],"this":[56],"paper,":[57],"we":[58],"propose":[59],"a":[60,168],"runtime":[61,131,149],"control":[62],"method,":[63],"called":[64],"DMS":[65,102,143,165,183],"(Dynamic":[66],"Model":[67],"Scaling),":[68],"enables":[70],"dynamic":[71],"resource-accuracy":[72,158],"trade-offs":[73],"support":[75,185],"various":[76],"QoS":[77],"requirements":[78],"applications.":[82],"DMS,":[84],"resource":[86,181],"demands":[87],"can":[92,121,144,184],"be":[93,122],"controlled":[94],"by":[95,108,166],"adaptive":[96],"pruning":[97,127],"computation-intensive":[99],"convolution":[100],"filters.":[101],"avoids":[103],"irregularity":[104],"pruned":[106],"models":[107,147],"reorganizing":[109],"filters":[110,120],"according":[111],"their":[113,156],"importance":[114],"so":[115],"varying":[117],"number":[118],"applied":[123],"efficiently.":[124],"Since":[125],"DMS\u2019s":[126],"method":[128],"incurs":[129],"no":[130],"overhead":[132],"preserves":[134],"full":[136],"capacity":[137],"original":[139],"models,":[142],"tailor":[145],"at":[148],"for":[150],"concurrent":[151],"applications":[154],"respective":[157],"trade-offs.":[159],"We":[160],"demonstrate":[161,173],"viability":[163],"implementing":[167],"prototype.":[169],"The":[170],"evaluation":[171],"results":[172],"that,":[174],"if":[175],"properly":[176],"coordinated":[177],"system":[179],"level":[180],"managers,":[182],"highly":[186],"robust":[187],"efficient":[189],"against":[192],"workloads.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
