{"id":"https://openalex.org/W2057796069","doi":"https://doi.org/10.1145/2483574.2483579","title":"Exploiting in-network processing for big data management","display_name":"Exploiting in-network processing for big data management","publication_year":2013,"publication_date":"2013-06-22","ids":{"openalex":"https://openalex.org/W2057796069","doi":"https://doi.org/10.1145/2483574.2483579","mag":"2057796069"},"language":"en","primary_location":{"id":"doi:10.1145/2483574.2483579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2483574.2483579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 SIGMOD/PODS Ph.D. symposium","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/A5049824486","display_name":"Lukas Rupprecht","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Lukas Rupprecht","raw_affiliation_strings":["Imperial College, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5049824486"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":2.4268,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.9112464,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998000264167786,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998000264167786,"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/T11478","display_name":"Caching and Content Delivery","score":0.9994000196456909,"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/T10273","display_name":"IoT and Edge/Fog Computing","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/computer-science","display_name":"Computer science","score":0.7283146381378174},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5326948165893555},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17381712794303894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7283146381378174},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5326948165893555},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17381712794303894}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2483574.2483579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2483574.2483579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 SIGMOD/PODS Ph.D. symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1491937446","https://openalex.org/W1536639265","https://openalex.org/W1563614747","https://openalex.org/W1969877208","https://openalex.org/W1978582625","https://openalex.org/W1981420413","https://openalex.org/W2003597767","https://openalex.org/W2053643516","https://openalex.org/W2056616673","https://openalex.org/W2074935284","https://openalex.org/W2077661716","https://openalex.org/W2087946700","https://openalex.org/W2103953076","https://openalex.org/W2104910040","https://openalex.org/W2110086534","https://openalex.org/W2126210439","https://openalex.org/W2130531694","https://openalex.org/W2144261930","https://openalex.org/W2144518192","https://openalex.org/W2147011911","https://openalex.org/W2150630976","https://openalex.org/W2155070484","https://openalex.org/W4232093111","https://openalex.org/W4237515752","https://openalex.org/W4256025236"],"related_works":["https://openalex.org/W280853923","https://openalex.org/W2577361510","https://openalex.org/W2901726430","https://openalex.org/W2368437561","https://openalex.org/W786186891","https://openalex.org/W3200249736","https://openalex.org/W2130579308","https://openalex.org/W398950355","https://openalex.org/W1996408511","https://openalex.org/W1434733837"],"abstract_inverted_index":{"Data":[0],"processing":[1,10,113],"systems":[2,114],"face":[3],"the":[4,16,22,59,71,93,100,104,120],"task":[5],"of":[6,61,73,99,119],"efficiently":[7],"storing":[8],"and":[9,46,91],"data":[11,45,62,83,112],"at":[12,63],"petabyte":[13],"scale,":[14],"with":[15],"amount":[17],"set":[18],"to":[19,43,70,85,116],"increase":[20],"in":[21,49,54],"future.":[23],"To":[24,102],"meet":[25],"such":[26],"a":[27,55,78,96,127],"requirement,":[28],"highly":[29],"scalable,":[30],"shared-nothing":[31],"systems,":[32],"e.g.":[33],"Google's":[34],"BigTable":[35],"[6]":[36],"or":[37],"Facebook's":[38],"Cassandra":[39],"[14],":[40],"are":[41],"built":[42],"partition":[44],"process":[47],"it":[48,107,125],"parallel":[50],"on":[51],"distributed":[52,111],"nodes":[53,90],"cluster.":[56],"This":[57],"allows":[58],"handling":[60],"scale":[64],"but":[65],"introduces":[66],"new":[67],"challenges":[68],"due":[69],"distribution":[72],"data.":[74],"Running":[75],"queries":[76],"involves":[77],"high":[79],"network":[80,94,105,121],"overhead":[81],"because":[82],"has":[84],"be":[86,117],"exchanged":[87],"between":[88],"cluster":[89],"hence,":[92],"becomes":[95],"critical":[97],"part":[98],"system.":[101],"avoid":[103],"bottleneck,":[106],"is":[108],"essential":[109],"for":[110],"(DDPS)":[115],"aware":[118],"rather":[122],"than":[123],"treating":[124],"as":[126],"black":[128],"box.":[129]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
