{"id":"https://openalex.org/W4405935354","doi":"https://doi.org/10.23919/cnsm62983.2024.10814515","title":"Link2Link: A Robust Probabilistic Routing Algorithm via Edge-centric Graph Reinforcement Learning","display_name":"Link2Link: A Robust Probabilistic Routing Algorithm via Edge-centric Graph Reinforcement Learning","publication_year":2024,"publication_date":"2024-10-28","ids":{"openalex":"https://openalex.org/W4405935354","doi":"https://doi.org/10.23919/cnsm62983.2024.10814515"},"language":"en","primary_location":{"id":"doi:10.23919/cnsm62983.2024.10814515","is_oa":false,"landing_page_url":"https://doi.org/10.23919/cnsm62983.2024.10814515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 20th International Conference on Network and Service Management (CNSM)","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/A5111735436","display_name":"Jingli Zhou","orcid":"https://orcid.org/0009-0001-7775-7154"},"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":"Jingli Zhou","raw_affiliation_strings":["Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014110901","display_name":"Yuqian Song","orcid":"https://orcid.org/0000-0002-8495-3487"},"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":"Yuqian Song","raw_affiliation_strings":["Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014730636","display_name":"Xinyuan Li","orcid":"https://orcid.org/0000-0001-5287-2335"},"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":"Xinyuan Li","raw_affiliation_strings":["Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101778892","display_name":"Wenli Zhou","orcid":"https://orcid.org/0000-0002-6786-1257"},"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":"Wenli Zhou","raw_affiliation_strings":["Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jun Liu","orcid":null},"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":"Jun Liu","raw_affiliation_strings":["Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Post and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.9785000085830688,"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":0.9785000085830688,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7706218957901001},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6925252079963684},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6147911548614502},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4928731918334961},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.47363463044166565},{"id":"https://openalex.org/keywords/routing-algorithm","display_name":"Routing algorithm","score":0.4689202904701233},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4249257743358612},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40439650416374207},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3866182565689087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27426594495773315},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1295468509197235},{"id":"https://openalex.org/keywords/routing-protocol","display_name":"Routing protocol","score":0.09327194094657898}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7706218957901001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6925252079963684},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6147911548614502},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4928731918334961},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.47363463044166565},{"id":"https://openalex.org/C2984173633","wikidata":"https://www.wikidata.org/wiki/Q22725","display_name":"Routing algorithm","level":4,"score":0.4689202904701233},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4249257743358612},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40439650416374207},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3866182565689087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27426594495773315},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1295468509197235},{"id":"https://openalex.org/C104954878","wikidata":"https://www.wikidata.org/wiki/Q1648707","display_name":"Routing protocol","level":3,"score":0.09327194094657898}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/cnsm62983.2024.10814515","is_oa":false,"landing_page_url":"https://doi.org/10.23919/cnsm62983.2024.10814515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 20th International Conference on Network and Service Management (CNSM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2116341502","https://openalex.org/W2132022337","https://openalex.org/W3100366369","https://openalex.org/W3187966659","https://openalex.org/W4226505429","https://openalex.org/W4226528404","https://openalex.org/W4232194410","https://openalex.org/W4244705237","https://openalex.org/W4245123941","https://openalex.org/W4380451036","https://openalex.org/W4388040530","https://openalex.org/W4389077666","https://openalex.org/W6741002519"],"related_works":["https://openalex.org/W2149224531","https://openalex.org/W4247716783","https://openalex.org/W2137646787","https://openalex.org/W2160885658","https://openalex.org/W2098791961","https://openalex.org/W2144164383","https://openalex.org/W2483530712","https://openalex.org/W4230539218","https://openalex.org/W2150731467","https://openalex.org/W2154215043"],"abstract_inverted_index":{"As":[0],"network":[1,43,90,123],"services":[2],"become":[3,9],"more":[4],"complex,":[5],"efficient":[6],"routing":[7,24,80,124],"has":[8],"crucial":[10],"for":[11,121],"ensuring":[12],"end-user":[13],"satisfaction.":[14],"To":[15,71],"address":[16],"this":[17,73],"challenge,":[18],"researchers":[19],"are":[20],"increasingly":[21],"turning":[22],"to":[23,55,84],"algorithms":[25,51],"that":[26,65,100],"integrate":[27],"Graph":[28],"Neural":[29],"Networks":[30],"(GNNs)":[31],"with":[32,49],"Deep":[33],"Reinforcement":[34],"Learning":[35],"(DRL),":[36],"leveraging":[37],"the":[38],"natural":[39],"graph":[40],"structure":[41],"of":[42],"topologies.":[44],"However,":[45],"a":[46,63,77,116],"significant":[47],"challenge":[48],"existing":[50],"is":[52,66],"their":[53],"inability":[54],"generalize":[56],"across":[57,105],"different":[58],"topologies":[59,91],"without":[60,111],"requiring":[61,112],"retraining,":[62,113],"constraint":[64],"impractical":[67],"in":[68],"real-world":[69],"applications.":[70],"overcome":[72],"limitation,":[74],"we":[75],"propose":[76],"novel":[78],"GNN-DRL-based":[79],"algorithm,":[81],"Link2Link,":[82],"designed":[83],"decouple":[85],"DRL-learned":[86],"knowledge":[87],"from":[88],"specific":[89],"by":[92],"focusing":[93],"on":[94],"link-level":[95],"features.":[96],"Extensive":[97],"experiments":[98],"demonstrate":[99],"Link2Link":[101],"achieves":[102],"robust":[103],"performance":[104],"diverse":[106],"topologies,":[107],"consistently":[108],"outperforming":[109],"OSPF":[110],"making":[114],"it":[115],"scalable":[117],"and":[118],"adaptable":[119],"solution":[120],"modern":[122],"challenges.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}