{"id":"https://openalex.org/W4401337837","doi":"https://doi.org/10.1109/iolts60994.2024.10616071","title":"Enhancing the Reliability of Split Computing Deep Neural Networks","display_name":"Enhancing the Reliability of Split Computing Deep Neural Networks","publication_year":2024,"publication_date":"2024-07-03","ids":{"openalex":"https://openalex.org/W4401337837","doi":"https://doi.org/10.1109/iolts60994.2024.10616071"},"language":"en","primary_location":{"id":"doi:10.1109/iolts60994.2024.10616071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iolts60994.2024.10616071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 30th International Symposium on On-Line Testing and Robust System Design (IOLTS)","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/A5041318100","display_name":"Giuseppe Esposito","orcid":"https://orcid.org/0000-0001-8687-3109"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Giuseppe Esposito","raw_affiliation_strings":["(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046650816","display_name":"Juan-David Guerrero-Balaguera","orcid":"https://orcid.org/0000-0001-6852-2372"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Juan-David Guerrero-Balaguera","raw_affiliation_strings":["(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107558399","display_name":"Josie E. Rodriguez Condia","orcid":"https://orcid.org/0000-0001-5957-5624"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Josie E. Rodriguez Condia","raw_affiliation_strings":["(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051196445","display_name":"Marco Levorato","orcid":"https://orcid.org/0000-0002-6920-4189"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marco Levorato","raw_affiliation_strings":["University of California,Computer Science Department,Irvine,US"],"affiliations":[{"raw_affiliation_string":"University of California,Computer Science Department,Irvine,US","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058555274","display_name":"M. Sonza Reorda","orcid":"https://orcid.org/0000-0003-2899-7669"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Matteo Sonza Reorda","raw_affiliation_strings":["(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"(DAUIN),Politecnico di Torino - Department of Control and Computer Engineering,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5041318100"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.5263,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64693206,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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":0.9976000189781189,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9968000054359436,"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/T10320","display_name":"Neural Networks and Applications","score":0.9959999918937683,"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":0.7552542686462402},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6649069786071777},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5969201326370239},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.42618703842163086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4218953251838684},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3449716567993164},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11181855201721191}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7552542686462402},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6649069786071777},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5969201326370239},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.42618703842163086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4218953251838684},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3449716567993164},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11181855201721191},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iolts60994.2024.10616071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iolts60994.2024.10616071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 30th International Symposium on On-Line Testing and Robust System Design (IOLTS)","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":27,"referenced_works":["https://openalex.org/W2083192461","https://openalex.org/W2294370754","https://openalex.org/W2393529948","https://openalex.org/W2901848761","https://openalex.org/W2963122961","https://openalex.org/W2965658867","https://openalex.org/W2969520618","https://openalex.org/W2971714613","https://openalex.org/W2982083293","https://openalex.org/W3008838787","https://openalex.org/W3029176123","https://openalex.org/W3036979375","https://openalex.org/W3046764219","https://openalex.org/W3134255974","https://openalex.org/W3149134903","https://openalex.org/W3187862527","https://openalex.org/W3195300140","https://openalex.org/W3215256528","https://openalex.org/W4242053016","https://openalex.org/W4251213825","https://openalex.org/W4280513934","https://openalex.org/W4285166740","https://openalex.org/W4290735104","https://openalex.org/W4297337546","https://openalex.org/W4319865974","https://openalex.org/W4386324016","https://openalex.org/W4399113861"],"related_works":["https://openalex.org/W2033512842","https://openalex.org/W4322734194","https://openalex.org/W3116237489","https://openalex.org/W4233600955","https://openalex.org/W2913665393","https://openalex.org/W2369695847","https://openalex.org/W3005535424","https://openalex.org/W2994319598","https://openalex.org/W2047067935","https://openalex.org/W1607054433"],"abstract_inverted_index":{"Artificial":[0],"intelligence":[1],"is":[2,99],"becoming":[3],"increasingly":[4],"popular":[5],"for":[6,65,175,186,204,210,219],"IoT":[7,40,84],"applications":[8],"in":[9,68,94],"safety-critical":[10,95],"fields":[11,96],"(e.g.,":[12],"autonomous":[13],"systems":[14],"and":[15,63,72,107,147,207],"biomedical,":[16],"robots).":[17],"Unfortunately,":[18],"the":[19,26,32,47,54,79,82,117,121,153,157,193],"inference\u2019s":[20],"workload":[21],"process":[22,56],"alone":[23],"increases":[24],"as":[25],"model":[27,174,185],"size":[28],"grows.":[29],"To":[30,160],"meet":[31],"computational":[33,86,106],"power":[34],"limitations":[35],"of":[36,57,81,123,135,152,156,172],"mobile":[37,70,103],"devices":[38,104],"running":[39],"applications,":[41],"modern":[42],"services":[43],"sometimes":[44],"resort":[45],"to":[46,119,167],"Split":[48,51,89,127,183],"Computing":[49,52,90,128,184],"paradigm.":[50],"divides":[53],"inference":[55],"a":[58,69,73,137,149,173,182],"Neural":[59],"Network":[60],"into":[61],"Head":[62],"Tail":[64],"their":[66,163],"execution":[67],"device":[71],"server,":[74],"respectively,":[75],"which":[76],"also":[77],"allows":[78],"reduction":[80],"overall":[83],"device\u2019s":[85],"cost.":[87],"Nonetheless,":[88],"can":[91],"be":[92],"used":[93],"where":[97],"reliability":[98],"crucial,":[100],"especially":[101],"when":[102,213],"have":[105],"cost":[108],"restrictions.":[109],"This":[110],"paper":[111],"introduces":[112],"hardening":[113,132,217],"techniques":[114,133],"acting":[115],"on":[116,126],"software":[118],"mitigate":[120],"effects":[122,199],"hardware":[124],"faults":[125],"models.":[129],"The":[130],"proposed":[131,194],"consist":[134],"i)":[136],"bounded":[138],"activation":[139],"function":[140],"whose":[141],"thresholds":[142],"are":[143],"refined":[144],"by":[145,200],"training,":[146],"ii)":[148],"per-channel":[150],"bounding":[151],"bottleneck":[154],"quantization":[155],"split":[158,170],"points.":[159],"quantitatively":[161],"assess":[162],"effectiveness,":[164],"we":[165,180],"resorted":[166],"two":[168],"different":[169],"configurations":[171],"image":[176,205],"classification.":[177],"In":[178],"addition,":[179],"considered":[181],"object":[187,211],"detection.":[188],"Our":[189],"findings":[190],"indicate":[191],"that":[192],"approaches":[195,218],"effectively":[196],"reduces":[197],"fault":[198],"$\\mathbf{3.":[201],"5":[202],"\\%}$":[203],"classifiers":[206],"$5.73":[208],"\\%$":[209],"detectors":[212],"compared":[214],"with":[215],"other":[216],"general":[220],"DNNs.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}