{"id":"https://openalex.org/W4405468623","doi":"https://doi.org/10.1145/3767295.3769362","title":"Canopy: Property-Driven Learning for Congestion Control","display_name":"Canopy: Property-Driven Learning for Congestion Control","publication_year":2026,"publication_date":"2026-04-24","ids":{"openalex":"https://openalex.org/W4405468623","doi":"https://doi.org/10.1145/3767295.3769362"},"language":"en","primary_location":{"id":"doi:10.1145/3767295.3769362","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767295.3769362","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st European Conference on Computer Systems","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3767295.3769362","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036100381","display_name":"Chenxi Yang","orcid":"https://orcid.org/0000-0003-0180-4126"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenxi Yang","raw_affiliation_strings":["UT Austin, Austin, USA"],"raw_orcid":"https://orcid.org/0009-0005-7352-9110","affiliations":[{"raw_affiliation_string":"UT Austin, Austin, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061115099","display_name":"Divyanshu Saxena","orcid":"https://orcid.org/0000-0002-7568-0624"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Divyanshu Saxena","raw_affiliation_strings":["UT Austin, Austin, USA"],"raw_orcid":"https://orcid.org/0000-0002-7568-0624","affiliations":[{"raw_affiliation_string":"UT Austin, Austin, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062717710","display_name":"Rohit Dwivedula","orcid":"https://orcid.org/0000-0002-2132-5707"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rohit Dwivedula","raw_affiliation_strings":["UT Austin, Austin, USA"],"raw_orcid":"https://orcid.org/0000-0002-2132-5707","affiliations":[{"raw_affiliation_string":"UT Austin, Austin, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088110132","display_name":"Kshiteej Mahajan","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kshiteej Mahajan","raw_affiliation_strings":["Google DeepMind, Mountain View, USA"],"raw_orcid":"https://orcid.org/0009-0002-5702-2836","affiliations":[{"raw_affiliation_string":"Google DeepMind, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057341982","display_name":"Swarat Chaudhuri","orcid":"https://orcid.org/0000-0002-6859-1391"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Swarat Chaudhuri","raw_affiliation_strings":["UT Austin, Austin, USA"],"raw_orcid":"https://orcid.org/0000-0002-6859-1391","affiliations":[{"raw_affiliation_string":"UT Austin, Austin, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035329776","display_name":"Aditya Akella","orcid":"https://orcid.org/0000-0002-5920-170X"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aditya Akella","raw_affiliation_strings":["UT Austin, Austin, USA"],"raw_orcid":"https://orcid.org/0000-0002-5920-170X","affiliations":[{"raw_affiliation_string":"UT Austin, Austin, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.00223532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1658","last_page":"1673"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.8356999754905701,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.8356999754905701,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5082659125328064},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.37901806831359863},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3367841839790344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5082659125328064},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.37901806831359863},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3367841839790344}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3767295.3769362","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767295.3769362","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st European Conference on Computer Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2412.10915","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.10915","pdf_url":"https://arxiv.org/pdf/2412.10915","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2412.10915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.10915","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1145/3767295.3769362","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767295.3769362","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st European Conference on Computer Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1364607497","display_name":"Expeditions: Collaborative Research: Understanding the World Through Code","funder_award_id":"1918651","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2721915658","display_name":null,"funder_award_id":"2326576","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7192131995","display_name":null,"funder_award_id":"2212559","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7395075087","display_name":null,"funder_award_id":"CCF-2212559","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7545490662","display_name":null,"funder_award_id":"CCF-1918651","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Learning-based":[0],"congestion":[1,35],"controllers":[2,19,36,106],"offer":[3,40],"better":[4,49],"adaptability":[5,109],"compared":[6],"to":[7,20,80],"traditional":[8],"heuristics.":[9],"However,":[10],"the":[11,46,68,82],"unreliability":[12],"of":[13,116],"learning":[14,63,69],"techniques":[15],"can":[16],"cause":[17],"learning-based":[18],"behave":[21],"poorly,":[22],"creating":[23],"a":[24,57,114],"need":[25],"for":[26,31],"formal":[27,65],"guarantees.":[28],"While":[29],"methods":[30,39],"formally":[32],"verifying":[33],"learned":[34,103],"exist,":[37],"these":[38],"binary":[41],"feedback":[42],"that":[43,61,100],"cannot":[44],"optimize":[45],"controller":[47],"toward":[48],"behavior.":[50],"We":[51],"improve":[52],"this":[53],"state-of-the-art":[54,102],"via":[55],"Canopy,":[56],"new":[58],"property-driven":[59],"framework":[60],"integrates":[62],"with":[64,76],"reasoning":[66],"in":[67],"loop.":[70],"Canopy":[71],"uses":[72],"novel":[73],"quantitative":[74],"certification":[75],"an":[77],"abstract":[78],"interpreter":[79],"guide":[81],"training":[83],"process,":[84],"rewarding":[85],"models,":[86],"and":[87,90,110],"evaluating":[88],"robust":[89],"safe":[91],"model":[92],"performance":[93],"on":[94],"worst-case":[95,111],"inputs.":[96],"Our":[97],"evaluation":[98],"demonstrates":[99],"unlike":[101],"controllers,":[104],"Canopy-trained":[105],"provide":[107],"both":[108],"reliability":[112],"across":[113],"range":[115],"network":[117],"conditions.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}