{"id":"https://openalex.org/W4416251862","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228635","title":"A Comparative Study of Graph-Based Learning Methods for Multivariate Time-Series Anomaly Detection in Cloud Microservice Applications","display_name":"A Comparative Study of Graph-Based Learning Methods for Multivariate Time-Series Anomaly Detection in Cloud Microservice Applications","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251862","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228635"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5076920288","display_name":"Ming Yu","orcid":"https://orcid.org/0000-0003-3703-9163"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Ming Yu","raw_affiliation_strings":["Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kevin O\u2019Shea","orcid":null},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Kevin O\u2019Shea","raw_affiliation_strings":["Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721128","display_name":"Yihan Li","orcid":"https://orcid.org/0000-0001-9485-8152"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihan Li","raw_affiliation_strings":["Wuhan University,School of Electronic Information,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University,School of Electronic Information,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112933564","display_name":"Sen Yan","orcid":"https://orcid.org/0000-0003-1919-7985"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Sen Yan","raw_affiliation_strings":["Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100448079","display_name":"Mingming Liu","orcid":"https://orcid.org/0000-0002-8988-2104"},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Mingming Liu","raw_affiliation_strings":["Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dublin City University,School of Electronic Engineering and the Research Ireland Insight Centre for Data Analytics,Dublin,Ireland","institution_ids":["https://openalex.org/I42934936"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9602000117301941,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9602000117301941,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.006899999920278788,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.005499999970197678,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.8263999819755554},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7788000106811523},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5509999990463257},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.44209998846054077},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.3903999924659729},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.3686000108718872},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.36309999227523804}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.8263999819755554},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7788000106811523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7488999962806702},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5509999990463257},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4771000146865845},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46160000562667847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44359999895095825},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.44209998846054077},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.36309999227523804},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.33660000562667847},{"id":"https://openalex.org/C2778505942","wikidata":"https://www.wikidata.org/wiki/Q18344624","display_name":"Microservices","level":3,"score":0.3240000009536743},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.26579999923706055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2614311976","https://openalex.org/W2743617586","https://openalex.org/W2756203131","https://openalex.org/W2884367066","https://openalex.org/W2903871660","https://openalex.org/W2927746189","https://openalex.org/W2963026768","https://openalex.org/W2963341956","https://openalex.org/W3034238904","https://openalex.org/W3034708216","https://openalex.org/W3080997787","https://openalex.org/W3093074257","https://openalex.org/W3171512724","https://openalex.org/W3208506679","https://openalex.org/W4282840064","https://openalex.org/W4285013180","https://openalex.org/W4296911935","https://openalex.org/W4311626519","https://openalex.org/W4311923017","https://openalex.org/W4313590336","https://openalex.org/W4365505337","https://openalex.org/W4387185768","https://openalex.org/W4391113910","https://openalex.org/W4391155025","https://openalex.org/W4391305513","https://openalex.org/W4392157869","https://openalex.org/W4397001512","https://openalex.org/W4401871988","https://openalex.org/W4402516174","https://openalex.org/W4402699695","https://openalex.org/W4402710947","https://openalex.org/W4408106464"],"related_works":[],"abstract_inverted_index":{"The":[0],"increasing":[1],"adoption":[2],"of":[3,61,82,103,140],"cloud":[4,51,141],"microservice":[5,35,142],"architectures":[6],"demands":[7],"robust":[8],"multivariate":[9],"time":[10,114],"series":[11],"anomaly":[12,134],"detection":[13,135],"algorithms":[14,23],"to":[15],"ensure":[16],"a":[17,58],"reliable":[18],"computing":[19],"infrastructure.":[20],"Although":[21],"numerous":[22],"are":[24,47],"readily":[25],"available":[26],"in":[27,34,137],"the":[28,80,89,127,138],"literature,":[29],"research":[30],"on":[31,119,121],"graph-based":[32,62,91,133],"methods":[33],"environments":[36],"remains":[37],"limited,":[38],"particularly":[39],"for":[40,50],"model":[41,128],"performance":[42],"and":[43,66,70,79,117,123],"training":[44,113],"efficiency,":[45],"which":[46],"both":[48],"critical":[49],"operators.":[52],"To":[53],"this":[54],"end,":[55],"we":[56],"present":[57],"comparative":[59],"study":[60],"methods,":[63],"assessing":[64],"supervised":[65],"hybrid":[67],"models,":[68],"with":[69,94],"without":[71,125],"graph":[72],"topology":[73],"information,":[74],"ensemble":[75,95],"versus":[76],"non-ensemble":[77],"approaches,":[78],"effectiveness":[81],"transfer":[83,110],"learning.":[84],"Our":[85],"results":[86],"demonstrate":[87],"that":[88],"proposed":[90],"method,":[92],"enhanced":[93],"learning,":[96],"achieves":[97],"an":[98],"average":[99,120],"event-wise":[100],"F1":[101],"score":[102],"0.89":[104],"across":[105],"two":[106],"proprietary":[107],"datasets.":[108],"Furthermore,":[109],"learning":[111],"reduced":[112],"by":[115],"43.27%":[116],"31.90%":[118],"CPU":[122],"GPU,":[124],"compromising":[126],"performance,":[129],"offering":[130],"insights":[131],"into":[132],"frameworks":[136],"context":[139],"applications.":[143]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}
