{"id":"https://openalex.org/W7156264211","doi":"https://doi.org/10.1145/3774904.3792448","title":"Alzo: Auto-Tuning with Reinforcement Learning for DAG-based Blockchains","display_name":"Alzo: Auto-Tuning with Reinforcement Learning for DAG-based Blockchains","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7156264211","doi":"https://doi.org/10.1145/3774904.3792448"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792448","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792448","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 ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792448","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017121545","display_name":"Qiuyu Ding","orcid":"https://orcid.org/0009-0001-3676-1552"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiuyu Ding","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-3676-1552","affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061105350","display_name":"Rongkai Zhang","orcid":"https://orcid.org/0009-0003-1652-7202"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongkai Zhang","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-1652-7202","affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051107722","display_name":"Qinnan Zhang","orcid":"https://orcid.org/0000-0001-9220-2694"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinnan Zhang","raw_affiliation_strings":["Institute of Artificial Intelligence, Beihang University, Beijing, China and Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9220-2694","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, Beihang University, Beijing, China and Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123964263","display_name":"Zhen Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Xiao","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6784-9709","affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017295101","display_name":"Jieyi Long","orcid":"https://orcid.org/0009-0007-4646-7131"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jieyi Long","raw_affiliation_strings":["Theta Labs, Inc., San Jose, USA"],"raw_orcid":"https://orcid.org/0009-0007-4646-7131","affiliations":[{"raw_affiliation_string":"Theta Labs, Inc., San Jose, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111057486","display_name":"Mingchao Wan","orcid":"https://orcid.org/0009-0007-7463-9922"},"institutions":[{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingchao Wan","raw_affiliation_strings":["Beijing Academy of Blockchain and Edge Computing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-7463-9922","affiliations":[{"raw_affiliation_string":"Beijing Academy of Blockchain and Edge Computing, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134712056","display_name":"Sen Liu","orcid":"https://orcid.org/0009-0002-1930-8534"},"institutions":[{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Liu","raw_affiliation_strings":["Beijing Academy of Blockchain and Edge Computing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-1930-8534","affiliations":[{"raw_affiliation_string":"Beijing Academy of Blockchain and Edge Computing, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5133509146","display_name":"Jin Dong","orcid":"https://orcid.org/0009-0006-9708-0220"},"institutions":[{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Dong","raw_affiliation_strings":["Beijing Academy of Blockchain and Edge Computing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-9708-0220","affiliations":[{"raw_affiliation_string":"Beijing Academy of Blockchain and Edge Computing, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5017121545"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.97767857,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5474","last_page":"5483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.510200023651123,"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"}},"topics":[{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.510200023651123,"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"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.15559999644756317,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.08229999989271164,"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/workflow","display_name":"Workflow","score":0.7089999914169312},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6866999864578247},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4377000033855438},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4180999994277954},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.40869998931884766},{"id":"https://openalex.org/keywords/interdependence","display_name":"Interdependence","score":0.39719998836517334},{"id":"https://openalex.org/keywords/human-in-the-loop","display_name":"Human-in-the-loop","score":0.3921000063419342},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.37940001487731934}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.743399977684021},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7089999914169312},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6866999864578247},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5727999806404114},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4377000033855438},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4180999994277954},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C185874996","wikidata":"https://www.wikidata.org/wiki/Q269699","display_name":"Interdependence","level":2,"score":0.39719998836517334},{"id":"https://openalex.org/C2780626000","wikidata":"https://www.wikidata.org/wiki/Q5936775","display_name":"Human-in-the-loop","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3603000044822693},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C2780565519","wikidata":"https://www.wikidata.org/wiki/Q1208937","display_name":"Multitude","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29980000853538513},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C119323957","wikidata":"https://www.wikidata.org/wiki/Q5048226","display_name":"Cascading failure","level":4,"score":0.27230000495910645},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792448","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792448","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 ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792448","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792448","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 ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6419479250907898,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2001912652","https://openalex.org/W2192203593","https://openalex.org/W2604122668","https://openalex.org/W2613206411","https://openalex.org/W2888705583","https://openalex.org/W2913127416","https://openalex.org/W2955804429","https://openalex.org/W2970851599","https://openalex.org/W3004629867","https://openalex.org/W3011974631","https://openalex.org/W3015450389","https://openalex.org/W3028852288","https://openalex.org/W3044147426","https://openalex.org/W3047676083","https://openalex.org/W3165341913","https://openalex.org/W3168892396","https://openalex.org/W3174969457","https://openalex.org/W3185672164","https://openalex.org/W3204939234","https://openalex.org/W3216073679","https://openalex.org/W4240422548","https://openalex.org/W4297964528","https://openalex.org/W4312037473","https://openalex.org/W4323343882","https://openalex.org/W4365795518","https://openalex.org/W4367721799","https://openalex.org/W4390512314","https://openalex.org/W4393253225","https://openalex.org/W4394717809","https://openalex.org/W4396758667"],"related_works":[],"abstract_inverted_index":{"As":[0],"critical":[1,88],"infrastructure":[2],"for":[3,11],"Web":[4],"3.0,":[5],"DAG-based":[6],"blockchains":[7],"promise":[8],"high":[9],"throughput":[10,123],"DeFi,":[12],"IoT,":[13],"and":[14,36,93,124],"DApps.":[15],"However,":[16],"realizing":[17],"this":[18,65],"potential":[19],"is":[20,25],"challenging,":[21],"as":[22],"system":[23],"performance":[24,84],"dictated":[26],"by":[27],"a":[28,54,101],"multitude":[29],"of":[30,108],"interdependent":[31],"parameters":[32,89],"across":[33],"network,":[34],"node,":[35],"consensus":[37],"layers.":[38],"Manual":[39],"configuration":[40,67],"fails":[41],"to":[42,44,48,63,86,104],"adapt":[43],"dynamic":[45],"workloads,":[46],"leading":[47],"suboptimal":[49],"performance.":[50],"We":[51],"introduce":[52],"Alzo,":[53],"novel":[55],"auto-tuner":[56],"that":[57,115],"employs":[58],"hierarchical":[59],"reinforcement":[60],"learning":[61],"(HRL)":[62],"navigate":[64],"complex":[66],"space.":[68],"By":[69],"decomposing":[70],"the":[71,106],"DAG":[72],"blockchain's":[73],"workflow":[74],"into":[75],"distinct":[76],"stages,":[77],"Alzo's":[78],"HRL":[79],"policy":[80],"learns":[81],"from":[82],"stage-level":[83],"metrics":[85],"control":[87],"governing":[90],"consensus,":[91],"execution,":[92],"graph":[94],"topology":[95],"in":[96],"real-time.":[97],"Furthermore,":[98],"we":[99],"employ":[100],"shadow-control":[102],"loop":[103],"ensure":[105],"safety":[107],"all":[109],"parameter":[110],"adjustments.":[111],"Our":[112],"experiments":[113],"show":[114],"Alzo":[116],"significantly":[117],"outperforms":[118],"other":[119],"configurations,":[120],"achieving":[121],"higher":[122],"lower":[125],"latency":[126],"under":[127],"variable":[128],"workloads":[129],"with":[130],"minimal":[131],"overhead.":[132]},"counts_by_year":[],"updated_date":"2026-04-28T06:12:00.211691","created_date":"2026-04-28T00:00:00"}