{"id":"https://openalex.org/W4386396862","doi":"https://doi.org/10.1145/3603269.3604865","title":"BitSense: Universal and Nearly Zero-Error Optimization for Sketch Counters with Compressive Sensing","display_name":"BitSense: Universal and Nearly Zero-Error Optimization for Sketch Counters with Compressive Sensing","publication_year":2023,"publication_date":"2023-09-01","ids":{"openalex":"https://openalex.org/W4386396862","doi":"https://doi.org/10.1145/3603269.3604865"},"language":"en","primary_location":{"id":"doi:10.1145/3603269.3604865","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3603269.3604865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGCOMM 2023 Conference","raw_type":"proceedings-article"},"type":"article","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/A5101990597","display_name":"Rui Ding","orcid":"https://orcid.org/0009-0006-7896-5840"},"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":"Rui Ding","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-7896-5840","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103024728","display_name":"Shibo Yang","orcid":"https://orcid.org/0009-0001-2282-3441"},"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":"Shibo Yang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-2282-3441","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011791240","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0002-0249-9664"},"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":"Xiang Chen","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0249-9664","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084512633","display_name":"Qun Huang","orcid":"https://orcid.org/0000-0002-2387-6131"},"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":"Qun Huang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2387-6131","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101990597"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":4.1411,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.95181168,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"220","last_page":"238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.998199999332428,"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/T11158","display_name":"Wireless Networks and Protocols","score":0.9972000122070312,"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/sketch","display_name":"Sketch","score":0.9122052192687988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7565683722496033},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7441413402557373},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5782393217086792},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.5226849317550659},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.493278443813324},{"id":"https://openalex.org/keywords/sketch-recognition","display_name":"Sketch recognition","score":0.48294585943222046},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3597084879875183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23967158794403076},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13348734378814697}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.9122052192687988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7565683722496033},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7441413402557373},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5782393217086792},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5226849317550659},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.493278443813324},{"id":"https://openalex.org/C132900626","wikidata":"https://www.wikidata.org/wiki/Q7534733","display_name":"Sketch recognition","level":4,"score":0.48294585943222046},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3597084879875183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23967158794403076},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13348734378814697},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.0},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3603269.3604865","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3603269.3604865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGCOMM 2023 Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.41999998688697815,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1946999620","display_name":null,"funder_award_id":"U20A20179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8439060332","display_name":null,"funder_award_id":"62172007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":60,"referenced_works":["https://openalex.org/W95608104","https://openalex.org/W1525485586","https://openalex.org/W1596849491","https://openalex.org/W2013431023","https://openalex.org/W2023797161","https://openalex.org/W2062159693","https://openalex.org/W2080234606","https://openalex.org/W2108909367","https://openalex.org/W2113935902","https://openalex.org/W2119667497","https://openalex.org/W2123845384","https://openalex.org/W2125472096","https://openalex.org/W2126120616","https://openalex.org/W2129638195","https://openalex.org/W2137376285","https://openalex.org/W2139151158","https://openalex.org/W2146012756","https://openalex.org/W2158498225","https://openalex.org/W2159068020","https://openalex.org/W2164452299","https://openalex.org/W2167450247","https://openalex.org/W2168595508","https://openalex.org/W2283556750","https://openalex.org/W2439904216","https://openalex.org/W2487095677","https://openalex.org/W2505539509","https://openalex.org/W2555471375","https://openalex.org/W2605823630","https://openalex.org/W2743723076","https://openalex.org/W2744693751","https://openalex.org/W2753629899","https://openalex.org/W2783033738","https://openalex.org/W2783425165","https://openalex.org/W2834288129","https://openalex.org/W2864823780","https://openalex.org/W2870014906","https://openalex.org/W2878215196","https://openalex.org/W2898344238","https://openalex.org/W2917789045","https://openalex.org/W2919413299","https://openalex.org/W2950087731","https://openalex.org/W2963885501","https://openalex.org/W2967106834","https://openalex.org/W2968108410","https://openalex.org/W2969998124","https://openalex.org/W2983654156","https://openalex.org/W3016758778","https://openalex.org/W3046191016","https://openalex.org/W3080797160","https://openalex.org/W3108496275","https://openalex.org/W3169567991","https://openalex.org/W3175189084","https://openalex.org/W3176348316","https://openalex.org/W4206137901","https://openalex.org/W4238185522","https://openalex.org/W4240091567","https://openalex.org/W4254937964","https://openalex.org/W4283323602","https://openalex.org/W4290991009","https://openalex.org/W6776064158"],"related_works":["https://openalex.org/W2294900353","https://openalex.org/W2411243951","https://openalex.org/W2151314278","https://openalex.org/W13629514","https://openalex.org/W1971224820","https://openalex.org/W2963977451","https://openalex.org/W2098836165","https://openalex.org/W1976890290","https://openalex.org/W1573697454","https://openalex.org/W2966897482"],"abstract_inverted_index":{"Sketch":[0],"algorithms":[1,64,121],"have":[2,149],"been":[3],"widely":[4],"deployed":[5],"for":[6,136],"network":[7],"measurement":[8,20],"as":[9,27,95],"they":[10],"achieve":[11],"high":[12],"accuracy":[13,190],"with":[14,80,124,163],"restricted":[15],"resource":[16],"usage.":[17],"They":[18],"store":[19],"results":[21],"compactly":[22],"in":[23,37,92,154],"fixed-size":[24],"counters.":[25,108],"However,":[26],"sketch":[28,52,82,93,120,165,179],"counters":[29,39,94],"are":[30],"skewed":[31],"towards":[32],"low":[33],"values,":[34],"higher":[35,90],"bits":[36,45,91],"most":[38],"remain":[40],"zero.":[41],"Such":[42],"massive":[43],"unused":[44],"impair":[46],"the":[47,58,125,146,174],"space":[48],"efficiency":[49],"valued":[50],"by":[51,181],"algorithms.":[53,83],"Unfortunately,":[54],"efforts":[55],"to":[56,62,88,104,115],"mitigate":[57],"issue":[59],"either":[60],"apply":[61],"specific":[63],"or":[65],"compromise":[66],"accuracy.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"design":[72],"BitSense,":[73],"a":[74,96,112,151,157],"novel":[75],"optimization":[76,195],"framework":[77],"that":[78,170],"integrates":[79],"existing":[81,178],"The":[84],"key":[85],"idea":[86],"is":[87],"regard":[89],"sparse":[97],"vector":[98],"and":[99,106,129,156,160,187],"leverage":[100],"compressive":[101],"sensing":[102],"techniques":[103],"compress":[105],"restore":[107],"Further,":[109],"BitSense":[110,152,171],"provides":[111],"programming":[113],"model":[114],"help":[116],"developers":[117],"easily":[118],"realize":[119],"without":[122],"dealing":[123],"details":[126],"of":[127,177],"compression":[128],"recovery.":[130],"Bit-Sense":[131],"proposes":[132],"an":[133],"automatic":[134],"approach":[135],"parameter":[137],"configuration.":[138,147],"It":[139],"theoretically":[140],"guarantees":[141],"nearly":[142],"zero":[143,189],"error":[144],"under":[145],"We":[148],"built":[150],"prototype":[153],"P4":[155],"software":[158],"platform":[159],"integrated":[161],"it":[162],"fourteen":[164],"solutions.":[166],"Extensive":[167],"experiments":[168],"show":[169],"significantly":[172],"reduces":[173],"memory":[175],"usage":[176],"solutions":[180],"25%-80%":[182],"while":[183],"incurring":[184],"little":[185],"overhead":[186],"almost":[188],"drop,":[191],"outperforming":[192],"five":[193],"state-of-the-art":[194],"frameworks.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
