{"id":"https://openalex.org/W2808705106","doi":"https://doi.org/10.1145/3219617.3219656","title":"Neural Network Meets DCN","display_name":"Neural Network Meets DCN","publication_year":2018,"publication_date":"2018-06-12","ids":{"openalex":"https://openalex.org/W2808705106","doi":"https://doi.org/10.1145/3219617.3219656","mag":"2808705106"},"language":"en","primary_location":{"id":"doi:10.1145/3219617.3219656","doi":"https://doi.org/10.1145/3219617.3219656","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3219617.3219656","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3219617.3219656","source":{"id":"https://openalex.org/S7407088608","display_name":"ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3219617.3219656","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001919662","display_name":"Mowei Wang","orcid":"https://orcid.org/0000-0001-9085-2247","observed_orcids":["https://orcid.org/0000-0001-9085-2247"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mowei Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091090025","display_name":"Yong Cui","orcid":"https://orcid.org/0000-0002-5171-739X","observed_orcids":["https://orcid.org/0000-0002-5171-739X"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Cui","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040041960","display_name":"Shihan Xiao","orcid":"https://orcid.org/0000-0001-9702-9130","observed_orcids":["https://orcid.org/0000-0001-9702-9130"]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihan Xiao","raw_affiliation_strings":["Huawei Technologies, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100328149","display_name":"Xin Wang","orcid":"https://orcid.org/0009-0004-1766-496X","observed_orcids":["https://orcid.org/0009-0004-1766-496X"]},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Wang","raw_affiliation_strings":["Stony Brook University, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University, New York, USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089740855","display_name":"Dan Yang","orcid":"https://orcid.org/0000-0002-9790-0851","observed_orcids":["https://orcid.org/0000-0002-9790-0851"]},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Yang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438001","display_name":"Kai Chen","orcid":"https://orcid.org/0000-0003-2587-6028","observed_orcids":["https://orcid.org/0000-0003-2587-6028"]},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kai Chen","raw_affiliation_strings":["Hong Kong University of Science and Technology, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100606993","display_name":"Jun Zhu","orcid":"https://orcid.org/0000-0002-1833-3917","observed_orcids":["https://orcid.org/0000-0002-1833-3917"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.8029,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.96471449,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"97","last_page":"99"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.8417999744415283,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.8417999744415283,"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/T10847","display_name":"Advanced Optical Network Technologies","score":0.06400000303983688,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.05620000138878822,"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/data-center-networks","display_name":"data center networks","score":0.9010000228881836},{"id":"https://openalex.org/keywords/network-reconfiguration","display_name":"network reconfiguration","score":0.781000018119812},{"id":"https://openalex.org/keywords/topology-optimization","display_name":"topology optimization","score":0.6830000281333923},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.6769999861717224},{"id":"https://openalex.org/keywords/flow-completion-time","display_name":"flow completion time","score":0.6880000233650208},{"id":"https://openalex.org/keywords/network-models","display_name":"network models","score":0.42800000309944153}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7688336968421936},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.6581400632858276},{"id":"https://openalex.org/C117729477","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Logical topology","level":3,"score":0.6336208581924438},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.6109792590141296},{"id":"https://openalex.org/C119701452","wikidata":"https://www.wikidata.org/wiki/Q5165881","display_name":"Control reconfiguration","level":2,"score":0.5250929594039917},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.48401400446891785},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4708033800125122},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46700915694236755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3071288466453552},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12267300486564636},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.10235574841499329},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3219617.3219656","doi":"https://doi.org/10.1145/3219617.3219656","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3219617.3219656","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3219617.3219656","source":{"id":"https://openalex.org/S7407088608","display_name":"ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-92976","doi":null,"is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2018&rft.spage=&rft.aulast=Wang&rft.aufirst=Mowei&rft.atitle=Neural%20Network%20Meets%20DCN%3A%20Traffic-driven%20Topology%20Adaptation%20with%20Deep%20Learning&rft.title=SIGMETRICS%202018%20-%20Abstracts%20of%20the%202018%20ACM%20International%20Conference%20on%20Measurement%20and%20Modeling%20of%20Computer%20Systems","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Book chapter"}],"best_oa_location":{"id":"doi:10.1145/3219617.3219656","doi":"https://doi.org/10.1145/3219617.3219656","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3219617.3219656","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3219617.3219656","source":{"id":"https://openalex.org/S7407088608","display_name":"ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G2144200491","display_name":"NeTS: Small: Fundamental Techniques for Incentive-aware, Efficient, and Reliable Cloudlet Management and Services","funder_award_id":"1526843","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/F4320326707","display_name":"State Grid Corporation of China","ror":"https://ror.org/05twwhs70"},{"id":"https://openalex.org/F4320335967","display_name":"Science and Technology Project of State Grid","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2808705106.pdf","grobid_xml":"https://content.openalex.org/works/W2808705106.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W587794757","https://openalex.org/W1442374986","https://openalex.org/W1677182931","https://openalex.org/W1698388015","https://openalex.org/W1746258828","https://openalex.org/W1988150362","https://openalex.org/W1998471240","https://openalex.org/W2007089612","https://openalex.org/W2016053056","https://openalex.org/W2022322548","https://openalex.org/W2059608229","https://openalex.org/W2062832101","https://openalex.org/W2076063813","https://openalex.org/W2097926925","https://openalex.org/W2115412108","https://openalex.org/W2116341502","https://openalex.org/W2119638333","https://openalex.org/W2124700175","https://openalex.org/W2126969025","https://openalex.org/W2129999749","https://openalex.org/W2130531694","https://openalex.org/W2131874158","https://openalex.org/W2141810662","https://openalex.org/W2143217585","https://openalex.org/W2151668565","https://openalex.org/W2155893237","https://openalex.org/W2157614013","https://openalex.org/W2163605009","https://openalex.org/W2164740236","https://openalex.org/W2168595508","https://openalex.org/W2170438678","https://openalex.org/W2174784067","https://openalex.org/W2177488376","https://openalex.org/W2257979135","https://openalex.org/W2299310877","https://openalex.org/W2311243340","https://openalex.org/W2312175257","https://openalex.org/W2418208970","https://openalex.org/W2486960733","https://openalex.org/W2504195863","https://openalex.org/W2519887557","https://openalex.org/W2530249205","https://openalex.org/W2604764118","https://openalex.org/W2613694343","https://openalex.org/W2742956305","https://openalex.org/W2743429249","https://openalex.org/W2759910885","https://openalex.org/W3160434771","https://openalex.org/W3161518659","https://openalex.org/W6977340213"],"related_works":["https://openalex.org/W4321433899","https://openalex.org/W2775085278","https://openalex.org/W3118033724","https://openalex.org/W4281718114","https://openalex.org/W6979270383","https://openalex.org/W4399912755","https://openalex.org/W4414838842","https://openalex.org/W4321488649","https://openalex.org/W4404952364","https://openalex.org/W3216160184"],"abstract_inverted_index":{"The":[0,135],"emerging":[1],"optical/wireless":[2],"topology":[3,31,55,66,103,120],"reconfiguration":[4],"technologies":[5],"have":[6],"shown":[7],"great":[8],"potential":[9],"in":[10,145],"improving":[11],"the":[12,29,35,52,65,76,86,95,99,107,116,139],"performance":[13,70,141],"of":[14,78,143],"data":[15,91,109],"center":[16],"networks.":[17],"However,":[18],"it":[19,82],"also":[20,125],"poses":[21],"a":[22,45,59],"big":[23],"challenge":[24],"on":[25],"how":[26],"to":[27,33,50,106],"find":[28],"best":[30],"configurations":[32,104],"support":[34],"dynamic":[36],"traffic":[37,88,100,133],"demands.":[38],"In":[39],"this":[40],"work,":[41],"we":[42],"present":[43],"xWeaver,":[44],"traffic-driven":[46],"deep":[47],"learning":[48],"solution":[49],"infer":[51],"high-performance":[53],"network":[54,61,73],"online.":[56],"xWeaver":[57,114,144],"supports":[58],"powerful":[60],"model":[62,129],"that":[63],"enables":[64],"optimization":[67],"over":[68],"different":[69],"metrics":[71],"and":[72,93,102,123],"architectures.":[74],"With":[75],"design":[77],"properly-structured":[79],"neural":[80],"networks,":[81],"can":[83,124],"automatically":[84],"derive":[85],"critical":[87],"patterns":[89,101],"from":[90],"traces":[92],"learn":[94],"underlying":[96],"mapping":[97],"between":[98],"specific":[105],"target":[108],"center.":[110],"After":[111],"offline":[112],"training,":[113],"generates":[115],"optimized":[117],"(or":[118],"near-optimal)":[119],"configuration":[121],"online,":[122],"smoothly":[126],"update":[127],"its":[128],"parameters":[130],"for":[131],"new":[132],"patterns.":[134],"experiment":[136],"results":[137],"show":[138],"significant":[140],"gain":[142],"supporting":[146],"smaller":[147],"flow":[148],"completion":[149],"time.":[150]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2018-06-21T00:00:00"}