{"id":"https://openalex.org/W4281689556","doi":"https://doi.org/10.1145/3489048.3522641","title":"Xatu","display_name":"Xatu","publication_year":2022,"publication_date":"2022-06-02","ids":{"openalex":"https://openalex.org/W4281689556","doi":"https://doi.org/10.1145/3489048.3522641"},"language":"en","primary_location":{"id":"doi:10.1145/3489048.3522641","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3489048.3522641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","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/A5110762810","display_name":"Yun Seong Nam","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yun Seong Nam","raw_affiliation_strings":["Purdue University & Google, Mountain View, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University & Google, Mountain View, IN, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067989679","display_name":"Jianfei Gao","orcid":"https://orcid.org/0009-0004-9804-4454"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianfei Gao","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037944350","display_name":"Chandan Bothra","orcid":"https://orcid.org/0009-0006-9674-4646"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chandan Bothra","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060690979","display_name":"Ehab Ghabashneh","orcid":"https://orcid.org/0000-0003-2254-9101"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ehab Ghabashneh","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073265856","display_name":"Sanjay Rao","orcid":"https://orcid.org/0000-0003-4825-4352"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjay Rao","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035917702","display_name":"Bruno Ribeiro","orcid":"https://orcid.org/0000-0002-3527-6192"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bruno Ribeiro","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110065597","display_name":"Jibin Zhan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jibin Zhan","raw_affiliation_strings":["Conviva, San Mateo, CA, USA"],"affiliations":[{"raw_affiliation_string":"Conviva, San Mateo, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100715414","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0001-8012-4684"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["Conviva, San Mateo, CA, USA"],"affiliations":[{"raw_affiliation_string":"Conviva, San Mateo, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5110762810"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":0.1007,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35490784,"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":"9","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":1.0,"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/T11165","display_name":"Image and Video Quality Assessment","score":1.0,"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/T10742","display_name":"Peer-to-Peer Network Technologies","score":0.9936000108718872,"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/T11478","display_name":"Caching and Content Delivery","score":0.9911999702453613,"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":0.8827123641967773},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6633110046386719},{"id":"https://openalex.org/keywords/emulation","display_name":"Emulation","score":0.5844041109085083},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.5624969005584717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4702188968658447},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4677453339099884},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46176570653915405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4502028822898865},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4304194748401642},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4186100959777832},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.19004151225090027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8827123641967773},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6633110046386719},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.5844041109085083},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.5624969005584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4702188968658447},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4677453339099884},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46176570653915405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4502028822898865},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4304194748401642},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4186100959777832},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.19004151225090027},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3489048.3522641","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3489048.3522641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4978335248","display_name":null,"funder_award_id":"ICE-T:RC 1836889, IIS-1943364, CCF-1918483","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"},{"id":"https://openalex.org/F4320307791","display_name":"Cisco Systems","ror":"https://ror.org/03yt1ez60"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W95608104","https://openalex.org/W1976944900","https://openalex.org/W2150453038","https://openalex.org/W2157394357","https://openalex.org/W2167407752","https://openalex.org/W2482797934","https://openalex.org/W2551396370","https://openalex.org/W2744628735","https://openalex.org/W2849781392","https://openalex.org/W2963191323","https://openalex.org/W2975425489","https://openalex.org/W6666761814","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W3087157779","https://openalex.org/W4306770904","https://openalex.org/W2105508921","https://openalex.org/W2348742136","https://openalex.org/W4231927834","https://openalex.org/W641208093","https://openalex.org/W3017054987","https://openalex.org/W2961085424","https://openalex.org/W3137229148","https://openalex.org/W4231884363"],"abstract_inverted_index":{"The":[0],"performance":[1,178],"of":[2,17,60,91],"Adaptive":[3],"Bitrate":[4],"(ABR)":[5],"algorithms":[6,185],"for":[7],"video":[8,18,64],"streaming":[9,65],"depends":[10],"on":[11,40,224],"accurately":[12],"predicting":[13],"the":[14,50,82,152],"download":[15,26,93],"time":[16],"chunks.":[19],"Existing":[20],"prediction":[21,101,109,163],"approaches":[22],"(i)":[23,69],"assume":[24],"chunk":[25,92],"times":[27,94],"are":[28,88],"dominated":[29],"by":[30,165],"network":[31,116,212],"throughput;":[32],"and":[33,42,44,77,136,155,193,207],"(ii)":[34,78],"apriori":[35,70],"cluster":[36],"sessions":[37,48,132],"(e.g.,":[38,143],"based":[39,223],"ISP":[41],"CDN)":[43],"only":[45],"learn":[46],"from":[47,62,74],"in":[49],"same":[51],"cluster.":[52],"We":[53,173],"make":[54],"three":[55],"contributions.":[56],"First,":[57],"through":[58],"analysis":[59],"data":[61],"real-world":[63],"sessions,":[66],"we":[67,104],"show":[68,158,174],"clustering":[71,124,128],"prevents":[72],"learning":[73],"related":[75],"clusters;":[76],"factors":[79],"such":[80],"as":[81],"Time":[83],"to":[84,168,202],"First":[85],"Byte":[86],"(TTFB)":[87],"key":[89],"components":[90],"but":[95],"not":[96],"easily":[97],"incorporated":[98],"into":[99],"existing":[100],"approaches.":[102],"Second,":[103],"propose":[105],"Xatu,":[106],"a":[107,114,208],"new":[108],"approach":[110],"that":[111,159],"jointly":[112],"learns":[113,127],"neural":[115,211],"sequence":[117],"model":[118],"with":[119,139,182,217],"an":[120,221],"interpretable":[121],"automatic":[122],"session":[123],"method.":[125],"Xatu":[126,160,175,215],"rules":[129],"across":[130],"all":[131],"it":[133],"deems":[134],"relevant,":[135],"models":[137],"sequences":[138],"multiple":[140,183],"chunk-dependent":[141],"features":[142],"TTFB)":[144],"rather":[145],"than":[146],"just":[147],"throughput.":[148],"Third,":[149],"evaluations":[150],"using":[151,198],"above":[153],"datasets":[154],"emulation":[156],"experiments":[157],"significantly":[161],"improves":[162],"accuracies":[164],"23.8%":[166],"relative":[167,201],"CS2P":[169],"(a":[170,188,195],"state-of-the-art":[171],"predictor).":[172],"provides":[176],"substantial":[177],"benefits":[179],"when":[180],"integrated":[181],"ABR":[184,191,222],"including":[186],"MPC":[187,218],"well":[189],"studied":[190],"algorithm),":[192],"FuguABR":[194],"recent":[196],"algorithm":[197],"stochastic":[199],"control)":[200],"their":[203],"default":[204],"predictors":[205],"(CS2P":[206],"fully":[209],"connected":[210],"respectively).":[213],"Further,":[214],"combined":[216],"outperforms":[219],"Pensieve,":[220],"deep":[225],"reinforcement":[226],"learning.":[227]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-06-13T00:00:00"}