{"id":"https://openalex.org/W7159634389","doi":"https://doi.org/10.48550/arxiv.2604.28175","title":"Strait: Perceiving Priority and Interference in ML Inference Serving","display_name":"Strait: Perceiving Priority and Interference in ML Inference Serving","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7159634389","doi":"https://doi.org/10.48550/arxiv.2604.28175"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.28175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28175","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.28175","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134930798","display_name":"Haidong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Haidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134957809","display_name":"Nikolaos Georgantas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Georgantas, Nikolaos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.22439999878406525,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.22439999878406525,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.13950000703334808,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.12250000238418579,"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/inference","display_name":"Inference","score":0.7391999959945679},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6462000012397766},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5982999801635742},{"id":"https://openalex.org/keywords/preemption","display_name":"Preemption","score":0.5232999920845032},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48339998722076416},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4269999861717224},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.41760000586509705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8209999799728394},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7391999959945679},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6462000012397766},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5982999801635742},{"id":"https://openalex.org/C206952183","wikidata":"https://www.wikidata.org/wiki/Q1193100","display_name":"Preemption","level":2,"score":0.5232999920845032},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4366999864578247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43070000410079956},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41819998621940613},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.41760000586509705},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.40549999475479126},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3986999988555908},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3409000039100647},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.328900009393692},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31610000133514404},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.31189998984336853},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.27970001101493835}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.28175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28175","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.28175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.28175","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"learning":[1],"(ML)":[2],"inference":[3,15,53],"serving":[4,44],"systems":[5],"host":[6],"deep":[7],"neural":[8],"network":[9],"(DNN)":[10],"models":[11,64],"and":[12,26,70],"schedule":[13],"incoming":[14],"requests":[16],"across":[17],"deployed":[18],"GPUs.":[19],"However,":[20],"limited":[21],"support":[22],"for":[23,51,72,105],"task":[24],"prioritization":[25],"insufficient":[27],"latency":[28,61],"estimation":[29],"under":[30,55,96],"concurrent":[31],"execution":[32,74],"may":[33],"restrict":[34],"their":[35],"applicability":[36],"in":[37],"on-premises":[38],"scenarios.":[39],"We":[40],"present":[41],"\\emph{Strait},":[42],"a":[43],"system":[45],"designed":[46],"to":[47,90,110,122],"enhance":[48],"deadline":[49,103],"satisfaction":[50],"dual-priority":[52],"traffic":[54],"high":[56],"GPU":[57],"utilization.":[58],"To":[59],"improve":[60],"estimation,":[62],"Strait":[63,101,126],"potential":[65],"contention":[66],"during":[67],"data":[68],"transfer":[69],"accounts":[71],"kernel":[73],"interference":[75],"through":[76],"an":[77],"adaptive":[78],"prediction":[79],"model.":[80],"By":[81],"drawing":[82],"on":[83,118],"these":[84],"predictions,":[85],"it":[86],"performs":[87],"priority-aware":[88],"scheduling":[89],"deliver":[91],"differentiated":[92],"handling.":[93],"Evaluation":[94],"results":[95],"intense":[97],"workloads":[98],"suggest":[99],"that":[100],"reduces":[102],"violations":[104],"high-priority":[106],"tasks":[107],"by":[108],"1.02":[109],"11.18":[111],"percentage":[112],"points":[113],"while":[114],"incurring":[115],"acceptable":[116],"costs":[117],"low-priority":[119],"tasks.":[120],"Compared":[121],"software-defined":[123],"preemption":[124],"approaches,":[125],"also":[127],"exhibits":[128],"more":[129],"equitable":[130],"performance.":[131]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-02T00:00:00"}
