{"id":"https://openalex.org/W4320024192","doi":"https://doi.org/10.1109/bigdata55660.2022.10020465","title":"SandPiper: A Cost-Efficient Adaptive Framework for Online Recommender Systems","display_name":"SandPiper: A Cost-Efficient Adaptive Framework for Online Recommender Systems","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4320024192","doi":"https://doi.org/10.1109/bigdata55660.2022.10020465"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020465","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020465","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5015124590","display_name":"Prashanth Thinakaran","orcid":"https://orcid.org/0000-0003-0861-2055"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Prashanth Thinakaran","raw_affiliation_strings":["The Pennsylvania State University"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073589054","display_name":"Kanak Mahadik","orcid":"https://orcid.org/0000-0002-6780-4199"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kanak Mahadik","raw_affiliation_strings":["Adobe Research"],"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104087483","display_name":"Jashwant Raj Gunasekaran","orcid":"https://orcid.org/0000-0001-9607-0131"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jashwant Gunasekaran","raw_affiliation_strings":["Adobe Research"],"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007116603","display_name":"Mahmut Kandemir","orcid":"https://orcid.org/0000-0002-9940-9951"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahmut Taylan Kandemir","raw_affiliation_strings":["The Pennsylvania State University"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054027488","display_name":"Chita R. Das","orcid":"https://orcid.org/0000-0002-4746-7578"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chita R. Das","raw_affiliation_strings":["The Pennsylvania State University"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5015124590"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.2079,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46272355,"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":"423","last_page":"430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7965515851974487},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.6239004135131836},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5297195911407471},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5042110681533813},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.48499032855033875},{"id":"https://openalex.org/keywords/stateless-protocol","display_name":"Stateless protocol","score":0.4758817255496979},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.44948986172676086},{"id":"https://openalex.org/keywords/online-algorithm","display_name":"Online algorithm","score":0.4199722409248352},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4173113703727722},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.22713050246238708},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22060632705688477},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1498555839061737},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.0968557596206665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7965515851974487},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.6239004135131836},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5297195911407471},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5042110681533813},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.48499032855033875},{"id":"https://openalex.org/C103613024","wikidata":"https://www.wikidata.org/wiki/Q230924","display_name":"Stateless protocol","level":3,"score":0.4758817255496979},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.44948986172676086},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.4199722409248352},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4173113703727722},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.22713050246238708},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22060632705688477},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1498555839061737},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0968557596206665},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020465","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020465","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W145683767","https://openalex.org/W2029469881","https://openalex.org/W2054141820","https://openalex.org/W2099419573","https://openalex.org/W2101234009","https://openalex.org/W2127492100","https://openalex.org/W2130978632","https://openalex.org/W2131889098","https://openalex.org/W2165599843","https://openalex.org/W2189162242","https://openalex.org/W2219888463","https://openalex.org/W2792630208","https://openalex.org/W2798820905","https://openalex.org/W2893890695","https://openalex.org/W2963361660","https://openalex.org/W2963964896","https://openalex.org/W2987607480","https://openalex.org/W3130104841","https://openalex.org/W3156636320","https://openalex.org/W6605931547","https://openalex.org/W6675354045","https://openalex.org/W6684489972","https://openalex.org/W6687241523","https://openalex.org/W6731729504","https://openalex.org/W6795223348"],"related_works":["https://openalex.org/W3040374273","https://openalex.org/W2955572513","https://openalex.org/W4360604845","https://openalex.org/W151293476","https://openalex.org/W2116712504","https://openalex.org/W2036359834","https://openalex.org/W3130948357","https://openalex.org/W2006651773","https://openalex.org/W2027050655","https://openalex.org/W3028244590"],"abstract_inverted_index":{"Online":[0],"recommender":[1,157],"systems":[2],"have":[3,6],"proven":[4],"to":[5,22,48,68,97,120,125,148,181,187,227,235],"ubiquitous":[7],"applications":[8],"in":[9,16,163],"various":[10],"domains.":[11],"To":[12,53],"provide":[13],"accurate":[14,150],"recommendations":[15],"real":[17],"time":[18,179],"it":[19,94,117],"is":[20,62,95,118],"imperative":[21],"constantly":[23],"train":[24],"and":[25,213,216],"deploy":[26],"models":[27],"with":[28],"the":[29,37,46,50,57,60,69,73,100,104,123,127,132,183,200,206,211,230,248,258],"latest":[30],"data":[31,44,74,189],"samples.":[32],"This":[33],"retraining":[34,106,176,233],"involves":[35],"adjusting":[36],"model":[38,47,105,175,197,207,232],"weights":[39],"by":[40],"incorporating":[41],"newly-arrived":[42],"streaming":[43],"into":[45],"bridge":[49,182],"accuracy":[51,133,184,209,250],"gap.":[52,134],"provision":[54],"resources":[55],"for":[56,155,224],"retraining,":[58],"typically":[59],"compute":[61],"hosted":[63],"on":[64,91,242],"VMs,":[65,85],"however,":[66],"due":[67,186],"dynamic":[70,221],"nature":[71],"of":[72,114],"arrival":[75],"patterns,":[76],"stateless":[77,101,146,225],"functions":[78,102,124,147,226],"would":[79],"be":[80],"an":[81,141,194],"ideal":[82],"alternative":[83],"over":[84],"as":[86],"they":[87],"can":[88],"instantaneously":[89],"scale":[90],"demand.":[92],"However,":[93],"non-trivial":[96],"statically":[98],"configure":[99,122],"because":[103],"exhibits":[107],"varying":[108],"resource":[109,128],"needs":[110],"during":[111],"different":[112],"phases":[113],"retraining.":[115],"Therefore,":[116],"crucial":[119],"dynamically":[121],"meet":[126],"requirements,":[129],"while":[130,204,253],"bridging":[131],"In":[135],"this":[136],"paper,":[137],"we":[138,167,192,218],"propose":[139,219],"Sandpiper,":[140],"adaptive":[142],"framework":[143],"that":[144,172,198,245],"leverages":[145],"deliver":[149],"predictions":[151],"at":[152,177],"low":[153],"cost":[154,214,237],"online":[156,195],"systems.":[158],"The":[159],"three":[160],"main":[161],"ideas":[162],"Sandpiper":[164,246],"are":[165],"(i)":[166],"design":[168],"a":[169,220],"data-drift":[170],"monitor":[171],"automatically":[173],"triggers":[174],"required":[178],"intervals":[180],"gap":[185],"incoming":[188],"drifts;":[190],"(ii)":[191],"develop":[193],"configuration":[196],"selects":[199],"appropriate":[201],"function":[202],"configurations":[203],"maintaining":[205],"serving":[208],"within":[210],"latency":[212],"budget;":[215],"(iii)":[217],"synchronization":[222],"policy":[223],"speed":[228],"up":[229],"distributed":[231],"leading":[234],"cloud":[236],"minimization.":[238],"A":[239],"prototype":[240],"implementation":[241],"AWS":[243],"shows":[244],"maintains":[247],"average":[249],"above":[251],"90%,":[252],"3.8\u00d7":[254],"less":[255],"expensive":[256],"than":[257],"traditional":[259],"VM-based":[260],"schemes.":[261]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
