{"id":"https://openalex.org/W4388470070","doi":"https://doi.org/10.1109/tnet.2023.3329357","title":"<i>xNet</i>: Modeling Network Performance With Graph Neural Networks","display_name":"<i>xNet</i>: Modeling Network Performance With Graph Neural Networks","publication_year":2023,"publication_date":"2023-11-07","ids":{"openalex":"https://openalex.org/W4388470070","doi":"https://doi.org/10.1109/tnet.2023.3329357"},"language":"en","primary_location":{"id":"doi:10.1109/tnet.2023.3329357","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnet.2023.3329357","pdf_url":null,"source":{"id":"https://openalex.org/S62238642","display_name":"IEEE/ACM Transactions on Networking","issn_l":"1063-6692","issn":["1063-6692","1558-2566"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Networking","raw_type":"journal-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/A5055998087","display_name":"Sijiang Huang","orcid":"https://orcid.org/0000-0001-5732-7459"},"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":true,"raw_author_name":"Sijiang Huang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5732-7459","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101317152","display_name":"Yunze Wei","orcid":"https://orcid.org/0009-0004-0618-512X"},"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":"Yunze Wei","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100311596","display_name":"Lingfeng Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingfeng Peng","raw_affiliation_strings":["China Mobile Research Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001919662","display_name":"Mowei Wang","orcid":"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":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9085-2247","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040579527","display_name":"Linbo Hui","orcid":"https://orcid.org/0000-0002-2841-2002"},"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":"Linbo Hui","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2841-2002","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346828","display_name":"Peng Liu","orcid":"https://orcid.org/0000-0002-5091-8464"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Liu","raw_affiliation_strings":["China Mobile Research Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048484469","display_name":"Zongpeng Du","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongpeng Du","raw_affiliation_strings":["China Mobile Research Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420220","display_name":"Zhenhua Liu","orcid":"https://orcid.org/0000-0003-2760-3621"},"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":"Zhenhua Liu","raw_affiliation_strings":["Huawei Technologies Company Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Company Ltd, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091090025","display_name":"Yong Cui","orcid":"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":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5171-739X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5055998087"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.3628,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82560538,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"32","issue":"2","first_page":"1753","last_page":"1767"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.9990000128746033,"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":0.9990000128746033,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9972000122070312,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9890999794006348,"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":0.8027024269104004},{"id":"https://openalex.org/keywords/network-simulation","display_name":"Network simulation","score":0.6021296977996826},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.562720537185669},{"id":"https://openalex.org/keywords/jitter","display_name":"Jitter","score":0.48757046461105347},{"id":"https://openalex.org/keywords/network-performance","display_name":"Network performance","score":0.48723354935646057},{"id":"https://openalex.org/keywords/network-model","display_name":"Network model","score":0.48026442527770996},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.47980359196662903},{"id":"https://openalex.org/keywords/network-planning-and-design","display_name":"Network planning and design","score":0.47700217366218567},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47533488273620605},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4548521637916565},{"id":"https://openalex.org/keywords/network-management","display_name":"Network management","score":0.45083558559417725},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.4180125594139099},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.37686049938201904},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3458538055419922},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3417363166809082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27535346150398254},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13723483681678772}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8027024269104004},{"id":"https://openalex.org/C139940560","wikidata":"https://www.wikidata.org/wiki/Q290036","display_name":"Network simulation","level":2,"score":0.6021296977996826},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.562720537185669},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.48757046461105347},{"id":"https://openalex.org/C203274722","wikidata":"https://www.wikidata.org/wiki/Q7001161","display_name":"Network performance","level":2,"score":0.48723354935646057},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.48026442527770996},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.47980359196662903},{"id":"https://openalex.org/C114563136","wikidata":"https://www.wikidata.org/wiki/Q19725982","display_name":"Network planning and design","level":2,"score":0.47700217366218567},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47533488273620605},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4548521637916565},{"id":"https://openalex.org/C129763632","wikidata":"https://www.wikidata.org/wiki/Q1454667","display_name":"Network management","level":2,"score":0.45083558559417725},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.4180125594139099},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.37686049938201904},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3458538055419922},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3417363166809082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27535346150398254},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13723483681678772},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnet.2023.3329357","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnet.2023.3329357","pdf_url":null,"source":{"id":"https://openalex.org/S62238642","display_name":"IEEE/ACM Transactions on Networking","issn_l":"1063-6692","issn":["1063-6692","1558-2566"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G7033924410","display_name":null,"funder_award_id":"62132009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7488493096","display_name":null,"funder_award_id":"62221003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W170020907","https://openalex.org/W1522301498","https://openalex.org/W1921523184","https://openalex.org/W2073787051","https://openalex.org/W2096544401","https://openalex.org/W2100785182","https://openalex.org/W2103830109","https://openalex.org/W2116341502","https://openalex.org/W2130531694","https://openalex.org/W2157331557","https://openalex.org/W2164740236","https://openalex.org/W2165698076","https://openalex.org/W2296407087","https://openalex.org/W2402144811","https://openalex.org/W2471288191","https://openalex.org/W2580909119","https://openalex.org/W2759910885","https://openalex.org/W2805516822","https://openalex.org/W2884601548","https://openalex.org/W2886938859","https://openalex.org/W2913856657","https://openalex.org/W2963154302","https://openalex.org/W2963549123","https://openalex.org/W2963943197","https://openalex.org/W2998280327","https://openalex.org/W3003671474","https://openalex.org/W3015370673","https://openalex.org/W3046744974","https://openalex.org/W3084983693","https://openalex.org/W3092894093","https://openalex.org/W3105771448","https://openalex.org/W3113087950","https://openalex.org/W3126135128","https://openalex.org/W4244705237","https://openalex.org/W4255485865","https://openalex.org/W4287641572","https://openalex.org/W4287645102","https://openalex.org/W4288091680","https://openalex.org/W6631190155","https://openalex.org/W6640185926","https://openalex.org/W6736126653","https://openalex.org/W6736685754","https://openalex.org/W6746060996","https://openalex.org/W6751350349","https://openalex.org/W6751796012","https://openalex.org/W6773718218","https://openalex.org/W6774033856","https://openalex.org/W6780226713","https://openalex.org/W6783741718"],"related_works":["https://openalex.org/W2055766740","https://openalex.org/W2374451912","https://openalex.org/W2348450208","https://openalex.org/W2355512483","https://openalex.org/W2390991816","https://openalex.org/W2592509926","https://openalex.org/W2358990811","https://openalex.org/W2394373447","https://openalex.org/W2276536874","https://openalex.org/W2387984143"],"abstract_inverted_index":{"Today\u2019s":[0],"network":[1,14,18,24,34,42,60,69,89,108,114,130,223],"is":[2,26,99,104],"notorious":[3],"for":[4,16,28,111],"its":[5,216],"complexity":[6],"and":[7,21,39,41,46,58,73,138,151,164,185],"uncertainty.":[8],"Network":[9],"operators":[10],"often":[11],"rely":[12],"on":[13,93],"models":[15,61],"efficient":[17],"planning,":[19],"operation,":[20],"optimization.":[22],"The":[23,171],"model":[25,109],"responsible":[27],"understanding":[29],"the":[30,66,120,129,144,157],"complex":[31],"relationships":[32],"between":[33,148],"performance":[35,181,192],"metrics":[36,182],"(e.g.,":[37,44],"delay":[38],"jitter)":[40],"characteristics":[43,131],"traffic":[45],"configuration).":[47],"However,":[48],"we":[49,84],"still":[50],"lack":[51],"a":[52,87,106,112,124,205],"systematic":[53],"approach":[54,126],"to":[55,127,155,194],"developing":[56],"accurate":[57],"lightweight":[59],"that":[62,102,175],"are":[63],"aware":[64],"of":[65,68,132,208,213,222],"impact":[67],"configurations":[70],"(i.e.,":[71,79],"expressiveness)":[72],"provide":[74],"fine-grained":[75,159],"flow-level":[76],"temporal":[77,184],"predictions":[78],"granularity).":[80],"In":[81],"this":[82],"paper,":[83],"propose":[85],"xNet,":[86],"data-driven":[88],"modeling":[90,128],"framework":[91],"based":[92],"graph":[94,136],"neural":[95],"networks":[96],"(GNN).":[97],"It":[98],"worth":[100],"noting":[101],"xNet":[103,122,142,166,176,203],"not":[105],"dedicated":[107],"designed":[110],"specific":[113],"scenario":[115],"with":[116,134,167,191,199],"constraint":[117],"considerations.":[118],"On":[119],"contrary,":[121],"provides":[123],"general":[125],"concern":[133],"relation":[135],"representations":[137],"configurable":[139],"GNN":[140],"blocks.":[141],"learns":[143],"state":[145],"transition":[146],"functions":[147],"time":[149],"steps":[150],"rolls":[152],"them":[153],"out":[154],"obtain":[156],"full":[158],"prediction":[160],"trajectory.":[161],"We":[162],"implement":[163],"instantiate":[165],"three":[168],"use":[169],"cases.":[170],"experimental":[172],"results":[173],"show":[174],"can":[177],"accurately":[178],"predict":[179],"different":[180,189],"(i.e.":[183],"steady-state":[186],"QoS)":[187],"in":[188,219],"scenarios,":[190],"comparable":[193],"state-of-the-art":[195],"domain-specific":[196],"models.":[197],"Compared":[198],"traditional":[200],"packet-level":[201],"simulators,":[202],"achieves":[204],"speed":[206],"improvement":[207],"more":[209],"than":[210],"two":[211],"orders":[212],"magnitude,":[214],"demonstrating":[215],"promising":[217],"application":[218],"real-time":[220],"optimization":[221],"configurations.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}