{"id":"https://openalex.org/W4383749396","doi":"https://doi.org/10.1109/ccgrid57682.2023.00027","title":"Layercake: Efficient Inference Serving with Cloud and Mobile Resources","display_name":"Layercake: Efficient Inference Serving with Cloud and Mobile Resources","publication_year":2023,"publication_date":"2023-05-01","ids":{"openalex":"https://openalex.org/W4383749396","doi":"https://doi.org/10.1109/ccgrid57682.2023.00027"},"language":"en","primary_location":{"id":"doi:10.1109/ccgrid57682.2023.00027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid57682.2023.00027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)","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/A5041264523","display_name":"Samuel S. Ogden","orcid":"https://orcid.org/0000-0003-2851-4129"},"institutions":[{"id":"https://openalex.org/I135369504","display_name":"California State University, Monterey Bay","ror":"https://ror.org/00mjdtw98","country_code":"US","type":"education","lineage":["https://openalex.org/I135369504"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samuel S. Ogden","raw_affiliation_strings":["California State University Monterey Bay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University Monterey Bay","institution_ids":["https://openalex.org/I135369504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051346938","display_name":"Tian Guo","orcid":"https://orcid.org/0000-0003-0060-2266"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Guo","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5173,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83497631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"191","last_page":"202"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9994999766349792,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9994999766349792,"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":0.9987999796867371,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.8555033206939697},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8506280183792114},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7730253338813782},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6134489178657532},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5970814228057861},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5277084708213806},{"id":"https://openalex.org/keywords/mobile-cloud-computing","display_name":"Mobile cloud computing","score":0.4572356343269348},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44719624519348145},{"id":"https://openalex.org/keywords/mobile-computing","display_name":"Mobile computing","score":0.4404803216457367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39964550733566284},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3318858742713928},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2792753279209137},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1113639771938324},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08680793642997742}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8555033206939697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8506280183792114},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7730253338813782},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6134489178657532},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5970814228057861},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5277084708213806},{"id":"https://openalex.org/C2779191767","wikidata":"https://www.wikidata.org/wiki/Q6887075","display_name":"Mobile cloud computing","level":3,"score":0.4572356343269348},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44719624519348145},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.4404803216457367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39964550733566284},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3318858742713928},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2792753279209137},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1113639771938324},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08680793642997742}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccgrid57682.2023.00027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid57682.2023.00027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G3935701615","display_name":null,"funder_award_id":"1755659,1815619,2105564,2236987","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W2102849319","https://openalex.org/W2119144962","https://openalex.org/W2183341477","https://openalex.org/W2279098554","https://openalex.org/W2321921970","https://openalex.org/W2734941459","https://openalex.org/W2742405391","https://openalex.org/W2747681982","https://openalex.org/W2889402930","https://openalex.org/W2913668833","https://openalex.org/W2949212852","https://openalex.org/W2949231165","https://openalex.org/W2962883027","https://openalex.org/W2963988417","https://openalex.org/W2964108773","https://openalex.org/W2983708784","https://openalex.org/W2998611528","https://openalex.org/W3026174634","https://openalex.org/W3088076788","https://openalex.org/W3094307698","https://openalex.org/W3095488153","https://openalex.org/W3097904259","https://openalex.org/W3101962329","https://openalex.org/W3107995663","https://openalex.org/W3156449479","https://openalex.org/W3156987284","https://openalex.org/W3162157550","https://openalex.org/W4205137559","https://openalex.org/W4233798301","https://openalex.org/W4236099117","https://openalex.org/W4297775537","https://openalex.org/W4302296459","https://openalex.org/W6637151318","https://openalex.org/W6677580257","https://openalex.org/W6695314431","https://openalex.org/W6730956707","https://openalex.org/W6737664043","https://openalex.org/W6747759466","https://openalex.org/W6753333537","https://openalex.org/W6753991380","https://openalex.org/W6754087033","https://openalex.org/W6762718338","https://openalex.org/W6765484274","https://openalex.org/W6779103662","https://openalex.org/W6798686915"],"related_works":["https://openalex.org/W3128807919","https://openalex.org/W3176411177","https://openalex.org/W2034905385","https://openalex.org/W2048100608","https://openalex.org/W3150868077","https://openalex.org/W4281385823","https://openalex.org/W2189508715","https://openalex.org/W3194052956","https://openalex.org/W2282963174","https://openalex.org/W4312728238"],"abstract_inverted_index":{"Many":[0],"mobile":[1,24,50,61],"applications":[2,25],"are":[3,77],"now":[4],"integrating":[5],"deep":[6],"learning":[7],"models":[8],"into":[9],"their":[10],"core":[11],"functionality.":[12],"These":[13],"functionalities":[14],"have":[15],"diverse":[16],"latency":[17,135],"requirements":[18],"while":[19,152],"demanding":[20],"high-accuracy":[21],"results.":[22],"Currently,":[23],"statically":[26],"decide":[27],"to":[28,69,139],"use":[29],"either":[30],"in-cloud":[31,163],"inference,":[32],"relying":[33,43],"on":[34,44],"a":[35,88],"fast":[36],"and":[37,98,110,114],"consistent":[38,56],"network,":[39],"or":[40,67],"on-device":[41],"execution,":[42],"sufficient":[45],"local":[46],"resources.":[47],"However,":[48],"neither":[49],"networks":[51],"nor":[52],"computation":[53],"resources":[54,158],"deliver":[55],"performance":[57,66,71],"in":[58,137],"practice.":[59],"Consequently,":[60],"inference":[62,74,90],"often":[63],"experiences":[64],"variable":[65],"struggles":[68],"meet":[70],"goals,":[72],"when":[73],"execution":[75],"decisions":[76],"not":[78],"made":[79],"dynamically.":[80],"In":[81],"this":[82,105],"paper,":[83],"we":[84],"introduce":[85],"Layer":[86],"Cake,":[87],"deep-learning":[89],"framework":[91],"that":[92],"dynamically":[93],"selects":[94],"the":[95,119,154],"best":[96],"model":[97,108,127],"location":[99],"for":[100,123],"executing":[101],"inferences.":[102],"Layercake":[103,133],"accomplishes":[104],"by":[106,159],"tracking":[107],"state":[109],"availability,":[111],"both":[112],"locally":[113],"remotely,":[115],"as":[116,118],"well":[117],"network":[120],"bandwidth,":[121],"allowing":[122],"accurate":[124],"estimations":[125],"of":[126,141,147,156],"response":[128],"time.":[129],"By":[130],"doing":[131],"so,":[132],"achieves":[134],"targets":[136],"up":[138],"96.4%":[140],"cases,":[142],"which":[143],"is":[144],"an":[145],"improvement":[146],"16.7%":[148],"over":[149,160],"similar":[150],"systems,":[151],"decreasing":[153],"cost":[155],"cloud-based":[157],"68.33%":[161],"than":[162],"inference.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
