{"id":"https://openalex.org/W7155000081","doi":"https://doi.org/10.1109/jiot.2026.3685317","title":"A Streaming Graph Hybrid Partitioning Method to Capture Multipatterns via the Incremental Lightweight GNN","display_name":"A Streaming Graph Hybrid Partitioning Method to Capture Multipatterns via the Incremental Lightweight GNN","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155000081","doi":"https://doi.org/10.1109/jiot.2026.3685317"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3685317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3685317","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5101785652","display_name":"Zhipeng Sun","orcid":"https://orcid.org/0000-0003-0999-370X"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Sun","raw_affiliation_strings":["School of Cyber Science and Engineering and Ningbo Key Laboratory of Information Technology Innovation and Security, Ningbo University of Technology, Ningbo, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering and Ningbo Key Laboratory of Information Technology Innovation and Security, Ningbo University of Technology, Ningbo, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134071776","display_name":"Chaoze Lu","orcid":"https://orcid.org/0000-0002-5134-196X"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoze Lu","raw_affiliation_strings":["School of Cyber Science and Engineering and Ningbo Key Laboratory of Information Technology Innovation and Security, Ningbo University of Technology, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0002-5134-196X","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering and Ningbo Key Laboratory of Information Technology Innovation and Security, Ningbo University of Technology, Ningbo, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051389232","display_name":"Dongdong Lv","orcid":"https://orcid.org/0000-0002-2737-7356"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongdong Lv","raw_affiliation_strings":["School of Artificial Intelligence, Ningbo University of Technology, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0002-2737-7356","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Ningbo University of Technology, Ningbo, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"last","author":{"id":null,"display_name":"Youli Fang","orcid":"https://orcid.org/0009-0003-2181-9306"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youli Fang","raw_affiliation_strings":["Department of Computer Science and Technology, Embedded System and Service Computing Key Laboratory of Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0003-2181-9306","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Embedded System and Service Computing Key Laboratory of Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.449155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"14","first_page":"30865","last_page":"30879"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.48809999227523804,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.48809999227523804,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.06859999895095825,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.0340999998152256,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/graph","display_name":"Graph","score":0.42570000886917114},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.33970001339912415},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.32829999923706055},{"id":"https://openalex.org/keywords/graph-partition","display_name":"Graph partition","score":0.32499998807907104},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.2766999900341034}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8396999835968018},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3912000060081482},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.32499998807907104},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.27000001072883606},{"id":"https://openalex.org/C2984822820","wikidata":"https://www.wikidata.org/wiki/Q1123036","display_name":"Processor scheduling","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.263700008392334},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3685317","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3685317","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1411194676","display_name":null,"funder_award_id":"23YJCZH159","funder_id":"https://openalex.org/F4320335982","funder_display_name":"Humanities and Social Science Fund of Ministry of Education of China"},{"id":"https://openalex.org/G3192321213","display_name":null,"funder_award_id":"2024J131","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"},{"id":"https://openalex.org/G5110796717","display_name":null,"funder_award_id":"2024J131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5742783504","display_name":null,"funder_award_id":"2023J180","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6389337410","display_name":null,"funder_award_id":"2023J180","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332587","display_name":"Natural Science Foundation of Ningbo","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335982","display_name":"Humanities and Social Science Fund of Ministry of Education of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"dynamic":[1,20,51,76,251],"big":[2],"graphs":[3],"becoming":[4],"mainstream":[5],"in":[6],"recent":[7],"years,":[8],"existing":[9],"graph":[10,29,52,66,77,92,109,130,139,187],"partitioning":[11,33,78,94,110,152,192,242,263,271],"methods":[12],"struggle":[13],"to":[14,28,45,96,145,196,254,259],"capture":[15,97],"the":[16,47,83,100,124,128,137,143,146,178,185,204,218,228,248,260],"complex":[17],"semantics":[18],"and":[19,40,116,134,136,168,199,208,224,250],"characteristics":[21,252],"of":[22,50,220,230],"streaming":[23,91,108,232,255,274],"graphs.":[24,233,256,275],"This":[25,210],"limitation":[26],"leads":[27],"<italic":[30,169],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[31,170],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>-way":[32],"outcomes":[34],"that":[35,120,237],"cannot":[36],"efficiently":[37],"support":[38],"parallel":[39],"distributed":[41],"computing,":[42],"thereby":[43],"failing":[44],"meet":[46],"high-performance":[48],"demands":[49],"processing.":[53],"Furthermore,":[54,257],"while":[55,244],"Graph":[56],"Neural":[57],"Networks":[58],"(GNNs)":[59],"have":[60],"achieved":[61],"remarkable":[62],"performance":[63,272],"across":[64],"various":[65],"computing":[67],"domains,":[68],"research":[69],"on":[70],"GNN":[71],"models":[72],"specifically":[73],"tailored":[74],"for":[75,160,273],"remains":[79],"scarce.":[80],"To":[81],"address":[82],"above":[84],"issues,":[85],"this":[86,158],"paper":[87],"introduces":[88],"SP_iLGNN,":[89],"a":[90],"hybrid":[93],"method":[95,105,267],"multi-patterns":[98],"via":[99],"incremental":[101,191,262],"lightweight":[102,148],"GNN.":[103],"Our":[104],"performs":[106],"online":[107,270],"over":[111],"multiple":[112],"consecutive":[113],"time":[114,126,176],"windows":[115],"formulates":[117],"an":[118,190],"objective":[119,153],"integrates":[121],"multi-patterns.":[122],"During":[123],"initial":[125,172],"window,":[127],"arrived":[129],"data":[131,140,198,222],"undergoes":[132,206],"augmentation":[133],"coarsening,":[135],"coarsened":[138],"serves":[141],"as":[142],"input":[144],"constructed":[147],"network":[149],"model.":[150],"The":[151],"is":[154,181,194],"then":[155],"integrated":[156],"with":[157],"model":[159,166,205],"joint":[161],"mini-batch":[162],"training,":[163],"yielding":[164],"optimized":[165],"parameters":[167],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>":[171],"partitions.":[173],"For":[174],"following":[175],"windows,":[177],"previous":[179],"partition":[180],"reused.":[182],"Guided":[183],"by":[184],"current":[186],"change":[188],"information,":[189],"step":[193],"applied":[195],"new":[197],"locally":[200],"affected":[201],"subgraphs.":[202],"Subsequently,":[203],"fine-tuning":[207],"updates.":[209],"methodology":[211],"avoids":[212],"expensive":[213],"retraining":[214],"from":[215],"scratch,":[216],"minimizes":[217],"scale":[219],"training":[221],"needed,":[223],"significantly":[225],"speeds":[226],"up":[227],"processing":[229],"subsequent":[231],"Extensive":[234],"experiments":[235],"indicate":[236],"SP_iLGNN":[238],"effectively":[239,246],"achieves":[240],"conventional":[241],"goals":[243],"more":[245],"maintaining":[247],"locality":[249],"inherent":[253],"compared":[258],"state-of-the-art":[261],"algorithm":[264],"iG-kway,":[265],"our":[266],"demonstrates":[268],"improved":[269]},"counts_by_year":[],"updated_date":"2026-07-09T05:49:46.723101","created_date":"2026-04-21T00:00:00"}