{"id":"https://openalex.org/W4390098565","doi":"https://doi.org/10.23919/wiopt58741.2023.10349831","title":"DOLL: Distributed OnLine Learning Using Preemptible Cloud Instances","display_name":"DOLL: Distributed OnLine Learning Using Preemptible Cloud Instances","publication_year":2023,"publication_date":"2023-08-24","ids":{"openalex":"https://openalex.org/W4390098565","doi":"https://doi.org/10.23919/wiopt58741.2023.10349831"},"language":"en","primary_location":{"id":"doi:10.23919/wiopt58741.2023.10349831","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/wiopt58741.2023.10349831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","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/A5102088093","display_name":"Harry Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Harry Jiang","raw_affiliation_strings":["Carnegie Mellon University,Department of Electrical and Computer Engineering,USA","Department of Electrical and Computer Engineering, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763625","display_name":"Xiaoxi Zhang","orcid":"https://orcid.org/0000-0003-0751-2773"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxi Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University,China","School of Computer Science and Engineering, Sun Yat-sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University,China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085243096","display_name":"Carlee Joe\u2010Wong","orcid":"https://orcid.org/0000-0003-0785-9291"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carlee Joe-Wong","raw_affiliation_strings":["Carnegie Mellon University,Department of Electrical and Computer Engineering,USA","Department of Electrical and Computer Engineering, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102088093"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.1748,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59024029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"175","last_page":"182"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9997000098228455,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9997000098228455,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994999766349792,"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":0.9962000250816345,"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":0.8734455704689026},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7483980655670166},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5063167810440063},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4864904284477234},{"id":"https://openalex.org/keywords/online-machine-learning","display_name":"Online machine learning","score":0.4377089738845825},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43601852655410767},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4253312945365906},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42123883962631226},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4149111211299896},{"id":"https://openalex.org/keywords/queueing-theory","display_name":"Queueing theory","score":0.4135902523994446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3779260218143463},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.20953050255775452},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13678541779518127},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1310262680053711},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.11831027269363403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8734455704689026},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7483980655670166},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5063167810440063},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4864904284477234},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.4377089738845825},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43601852655410767},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4253312945365906},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42123883962631226},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4149111211299896},{"id":"https://openalex.org/C22684755","wikidata":"https://www.wikidata.org/wiki/Q847526","display_name":"Queueing theory","level":2,"score":0.4135902523994446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3779260218143463},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.20953050255775452},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13678541779518127},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1310262680053711},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.11831027269363403},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/wiopt58741.2023.10349831","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/wiopt58741.2023.10349831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","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":39,"referenced_works":["https://openalex.org/W1988580225","https://openalex.org/W2107438106","https://openalex.org/W2130062883","https://openalex.org/W2336721351","https://openalex.org/W2521140588","https://openalex.org/W2544661862","https://openalex.org/W2605643718","https://openalex.org/W2734358244","https://openalex.org/W2807786182","https://openalex.org/W2891635827","https://openalex.org/W2940920241","https://openalex.org/W2952215077","https://openalex.org/W2963739929","https://openalex.org/W2979325626","https://openalex.org/W3011164818","https://openalex.org/W3021435406","https://openalex.org/W3023085450","https://openalex.org/W3025118830","https://openalex.org/W3037843194","https://openalex.org/W3047261146","https://openalex.org/W3090734853","https://openalex.org/W3137236623","https://openalex.org/W3173185171","https://openalex.org/W3189317289","https://openalex.org/W4225004481","https://openalex.org/W4234975092","https://openalex.org/W4246900739","https://openalex.org/W4388297583","https://openalex.org/W4388469753","https://openalex.org/W4390098565","https://openalex.org/W6676105031","https://openalex.org/W6679314259","https://openalex.org/W6680196509","https://openalex.org/W6755020399","https://openalex.org/W6762049204","https://openalex.org/W6787395356","https://openalex.org/W6791518594","https://openalex.org/W6810520696","https://openalex.org/W6931906425"],"related_works":["https://openalex.org/W2163664144","https://openalex.org/W2118190631","https://openalex.org/W2899532525","https://openalex.org/W4389775782","https://openalex.org/W4394734788","https://openalex.org/W4213079490","https://openalex.org/W2913715341","https://openalex.org/W114517082","https://openalex.org/W2165651264","https://openalex.org/W4323366756"],"abstract_inverted_index":{"To":[0],"defray":[1],"the":[2,34,43,84,92,99,173],"increasingly":[3],"massive":[4],"costs":[5],"of":[6,25,55,113,143,175],"running":[7,16],"large":[8,141],"machine":[9,27,50,118],"learning":[10,51,119],"workloads,":[11],"much":[12,46],"work":[13,101],"has":[14],"proposed":[15],"them":[17],"on":[18,68,121,193,202],"preemptible":[19,69,122,177],"cloud":[20,35],"instances,":[21],"a":[22,107,111,117],"discount":[23],"tier":[24],"virtual":[26],"rentals":[28],"that":[29,45,109],"may":[30,79],"be":[31],"interrupted":[32],"at":[33],"provider's":[36],"discretion.":[37],"This":[38],"work,":[39],"however,":[40],"largely":[41],"ignores":[42],"fact":[44],"data":[47,75,151],"used":[48],"for":[49,163],"comes":[52],"from":[53],"streams":[54],"diverse":[56],"sources,":[57],"e.g.,":[58],"wirelessly":[59],"connected":[60],"cameras":[61],"or":[62],"hospital":[63],"health":[64],"records.":[65],"Processing":[66],"datastreams":[67,114],"instances":[70,93,180],"presents":[71],"new":[72],"challenges:":[73],"processing":[74],"as":[76,147,149],"they":[77],"arrive":[78],"engender":[80],"bottlenecks":[81],"when":[82],"scaling":[83],"system":[85,108],"to":[86,102,115,131,140,171],"handle":[87],"higher":[88],"throughput,":[89],"particularly":[90],"if":[91],"are":[94,160],"frequently":[95],"interrupted.":[96],"Ours":[97],"is":[98,191],"first":[100],"design,":[103],"analyze,":[104],"and":[105,129,133,145,178,185],"optimize":[106,172],"uses":[110,127],"set":[112],"train":[116],"model":[120,203],"instances.":[123],"Our":[124],"system,":[125],"DOLL,":[126],"queueing":[128],"batching":[130],"parallelize":[132],"scale":[134],"SGD":[135],"(stochastic":[136],"gradient":[137],"descent)-based":[138],"optimizers":[139],"numbers":[142],"workers":[144],"datastreams,":[146],"well":[148],"heterogeneous":[150],"arrival":[152],"rates":[153],"across":[154],"streams.":[155],"Expected":[156],"error":[157,183],"convergence":[158],"guarantees":[159],"then":[161],"derived":[162],"DOLL's":[164],"training":[165],"process.":[166],"We":[167],"use":[168],"this":[169,189],"guarantee":[170],"cost":[174,197],"requisitioning":[176],"on-demand":[179],"given":[181],"an":[182],"target":[184],"wall-clock":[186],"time":[187],"deadline;":[188],"optimization":[190],"validated":[192],"experiments":[194],"demonstrating":[195],"substantial":[196],"savings":[198],"with":[199],"little":[200],"impact":[201],"error.":[204]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}