{"id":"https://openalex.org/W3009921999","doi":"https://doi.org/10.1109/globecom38437.2019.9013742","title":"Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning","display_name":"Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3009921999","doi":"https://doi.org/10.1109/globecom38437.2019.9013742","mag":"3009921999"},"language":"en","primary_location":{"id":"doi:10.1109/globecom38437.2019.9013742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom38437.2019.9013742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5082788397","display_name":"Chengshuai Shi","orcid":"https://orcid.org/0000-0002-2727-8251"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]},{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chengshuai Shi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, USA","Department of Electrical and Computer Engineering, University of Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085364987","display_name":"Lixing Chen","orcid":"https://orcid.org/0000-0002-1805-0183"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lixing Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016749653","display_name":"Cong Shen","orcid":"https://orcid.org/0000-0002-3148-4453"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cong Shen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035185924","display_name":"Linqi Song","orcid":"https://orcid.org/0000-0003-2756-4984"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Linqi Song","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044771462","display_name":"Jie Xu","orcid":"https://orcid.org/0000-0002-0515-1647"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Miami, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Miami, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9977999925613403,"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":0.9969000220298767,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8678659796714783},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.746874213218689},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.6937296986579895},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6351152658462524},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.6129637360572815},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.573149561882019},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5602075457572937},{"id":"https://openalex.org/keywords/mobile-edge-computing","display_name":"Mobile edge computing","score":0.5309892296791077},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48529475927352905},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.4754495322704315},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4514273405075073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4202442765235901},{"id":"https://openalex.org/keywords/lyapunov-optimization","display_name":"Lyapunov optimization","score":0.41418761014938354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34721046686172485},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.31161853671073914},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.2290259301662445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8678659796714783},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.746874213218689},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.6937296986579895},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6351152658462524},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.6129637360572815},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.573149561882019},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5602075457572937},{"id":"https://openalex.org/C2776061582","wikidata":"https://www.wikidata.org/wiki/Q25325231","display_name":"Mobile edge computing","level":3,"score":0.5309892296791077},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48529475927352905},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.4754495322704315},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4514273405075073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4202442765235901},{"id":"https://openalex.org/C101403955","wikidata":"https://www.wikidata.org/wiki/Q6707083","display_name":"Lyapunov optimization","level":5,"score":0.41418761014938354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34721046686172485},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.31161853671073914},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.2290259301662445},{"id":"https://openalex.org/C37935115","wikidata":"https://www.wikidata.org/wiki/Q6707085","display_name":"Lyapunov redesign","level":4,"score":0.0},{"id":"https://openalex.org/C191544260","wikidata":"https://www.wikidata.org/wiki/Q1238630","display_name":"Lyapunov exponent","level":3,"score":0.0},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/globecom38437.2019.9013742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom38437.2019.9013742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},{"id":"mag:3041288084","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002255605678550","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1915485278","https://openalex.org/W2051267297","https://openalex.org/W2137152139","https://openalex.org/W2163605009","https://openalex.org/W2285660444","https://openalex.org/W2462428341","https://openalex.org/W2594560857","https://openalex.org/W2604119386","https://openalex.org/W2605258629","https://openalex.org/W2612445135","https://openalex.org/W2624989916","https://openalex.org/W2809251854","https://openalex.org/W2811166235","https://openalex.org/W2886576854","https://openalex.org/W2949866693","https://openalex.org/W2962883027","https://openalex.org/W2963981420","https://openalex.org/W2963989815","https://openalex.org/W3099785009","https://openalex.org/W3106445841","https://openalex.org/W3118608800","https://openalex.org/W4235435541","https://openalex.org/W4289729785","https://openalex.org/W4297775537","https://openalex.org/W6684191040","https://openalex.org/W6718750956","https://openalex.org/W6724998850"],"related_works":["https://openalex.org/W4320029583","https://openalex.org/W4284671922","https://openalex.org/W2944535814","https://openalex.org/W4311866176","https://openalex.org/W4361251304","https://openalex.org/W2897042868","https://openalex.org/W3203523248","https://openalex.org/W4206585306","https://openalex.org/W2907086092","https://openalex.org/W4287646874"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2],"witnessed":[3],"deep":[4],"neural":[5],"networks":[6],"(DNNs)":[7],"become":[8],"the":[9,51,62,65,69,75,89,95,100,108,119,127,143,163,166],"de":[10],"facto":[11],"tool":[12],"in":[13,28,47,103,121],"many":[14],"applications":[15],"such":[16],"as":[17],"image":[18],"classification":[19],"and":[20,64,99,132,148],"speech":[21],"recognition.":[22],"But":[23],"significant":[24],"unmet":[25],"needs":[26],"remain":[27],"performing":[29],"DNN":[30,41,92,120],"inference":[31,42,96],"tasks":[32,43],"on":[33,94,107],"mobile":[34,52,66,136],"devices.":[35,137],"Although":[36],"edge":[37,63,78,104],"computing":[38],"enables":[39],"complex":[40],"to":[44,50,74,125,161],"be":[45],"performed":[46],"close":[48],"proximity":[49],"device,":[53],"performance":[54,98,131,152],"optimization":[55,146],"requires":[56],"a":[57,150,157],"carefully":[58],"designed":[59,141],"synergy":[60],"between":[61,130],"device.":[67],"Moreover,":[68],"confidentiality":[70],"of":[71,81,91,165],"uploaded":[72],"data":[73],"possibly":[76],"untrusted":[77],"server":[79],"is":[80,140],"great":[82],"concern.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87,111,155],"investigate":[88],"impact":[90],"partitioning":[93],"latency":[97],"privacy":[101,133],"risks":[102],"computing.":[105],"Based":[106],"obtained":[109],"insights,":[110],"design":[112],"an":[113],"offloading":[114,168],"strategy":[115,139],"that":[116],"adaptively":[117],"partitions":[118],"varying":[122],"network":[123],"environments":[124],"make":[126],"optimal":[128],"tradeoff":[129],"for":[134],"battery-powered":[135],"This":[138],"under":[142],"learning-aided":[144],"Lyapunov":[145],"framework":[147],"has":[149],"provable":[151],"guarantee.":[153],"Finally,":[154],"build":[156],"small-":[158],"scale":[159],"testbed":[160],"demonstrate":[162],"efficacy":[164],"proposed":[167],"scheme.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
