{"id":"https://openalex.org/W4205613083","doi":"https://doi.org/10.3390/bdcc6010005","title":"A Hierarchical Hadoop Framework to Process Geo-Distributed Big Data","display_name":"A Hierarchical Hadoop Framework to Process Geo-Distributed Big Data","publication_year":2022,"publication_date":"2022-01-06","ids":{"openalex":"https://openalex.org/W4205613083","doi":"https://doi.org/10.3390/bdcc6010005"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc6010005","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc6010005","pdf_url":"https://www.mdpi.com/2504-2289/6/1/5/pdf?version=1641440395","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-2289/6/1/5/pdf?version=1641440395","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089770971","display_name":"Giuseppe Modica","orcid":"https://orcid.org/0000-0002-0298-7828"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Di Modica","raw_affiliation_strings":["Department of Computer Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056164318","display_name":"Orazio Tomarchio","orcid":"https://orcid.org/0000-0003-4653-0480"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Orazio Tomarchio","raw_affiliation_strings":["Department of Electrical, Electronic and Computer Engineering, University of Catania, Viale A. Doria 6, 95125 Catania, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electrical, Electronic and Computer Engineering, University of Catania, Viale A. Doria 6, 95125 Catania, Italy","institution_ids":["https://openalex.org/I39063666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056164318"],"corresponding_institution_ids":["https://openalex.org/I39063666"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.212,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82284909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"6","issue":"1","first_page":"5","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9990000128746033,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9965000152587891,"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":0.8403667211532593},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.7482768297195435},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6943817734718323},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.6221524477005005},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5237700343132019},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5075439214706421},{"id":"https://openalex.org/keywords/data-intensive-computing","display_name":"Data-intensive computing","score":0.5027234554290771},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.45740559697151184},{"id":"https://openalex.org/keywords/grid-computing","display_name":"Grid computing","score":0.21320369839668274},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1927385926246643},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15820735692977905}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8403667211532593},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.7482768297195435},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6943817734718323},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.6221524477005005},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5237700343132019},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5075439214706421},{"id":"https://openalex.org/C76831024","wikidata":"https://www.wikidata.org/wiki/Q5227096","display_name":"Data-intensive computing","level":4,"score":0.5027234554290771},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.45740559697151184},{"id":"https://openalex.org/C70429105","wikidata":"https://www.wikidata.org/wiki/Q249999","display_name":"Grid computing","level":3,"score":0.21320369839668274},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1927385926246643},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15820735692977905},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/bdcc6010005","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc6010005","pdf_url":"https://www.mdpi.com/2504-2289/6/1/5/pdf?version=1641440395","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:cris.unibo.it:11585/906032","is_oa":true,"landing_page_url":"https://www.mdpi.com/2504-2289/6/1/5","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:bbe69c5b0cd14310b63a2a647459f051","is_oa":true,"landing_page_url":"https://doaj.org/article/bbe69c5b0cd14310b63a2a647459f051","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing, Vol 6, Iss 1, p 5 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2504-2289/6/1/5/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/bdcc6010005","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 5","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/bdcc6010005","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc6010005","pdf_url":"https://www.mdpi.com/2504-2289/6/1/5/pdf?version=1641440395","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5400000214576721,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205613083.pdf","grobid_xml":"https://content.openalex.org/works/W4205613083.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1578015699","https://openalex.org/W1668361395","https://openalex.org/W1968801596","https://openalex.org/W1973747955","https://openalex.org/W1987671078","https://openalex.org/W2064349969","https://openalex.org/W2072129576","https://openalex.org/W2076684951","https://openalex.org/W2084667297","https://openalex.org/W2086392024","https://openalex.org/W2087133653","https://openalex.org/W2112658241","https://openalex.org/W2148453719","https://openalex.org/W2149140091","https://openalex.org/W2151763581","https://openalex.org/W2154894831","https://openalex.org/W2259941770","https://openalex.org/W2295019192","https://openalex.org/W2329835557","https://openalex.org/W2497069692","https://openalex.org/W2515896452","https://openalex.org/W2556111255","https://openalex.org/W2558667100","https://openalex.org/W2559559327","https://openalex.org/W2580245708","https://openalex.org/W2612282432","https://openalex.org/W2731964388","https://openalex.org/W2789263069","https://openalex.org/W2970435764","https://openalex.org/W2970978109","https://openalex.org/W3042962150","https://openalex.org/W3106036258","https://openalex.org/W3142038251"],"related_works":["https://openalex.org/W2883256816","https://openalex.org/W2171408034","https://openalex.org/W3003320923","https://openalex.org/W2106140982","https://openalex.org/W2152313554","https://openalex.org/W3048672182","https://openalex.org/W1509300825","https://openalex.org/W2895998809","https://openalex.org/W2794953737","https://openalex.org/W3216647085"],"abstract_inverted_index":{"In":[0,107,179],"the":[1,26,51,72,77,82,108,115,122,130,163,166,177,184,187,192,196,204,211,214,219,227,242,246],"past":[2],"twenty":[3],"years,":[4],"we":[5,190,221],"have":[6,85,111,147],"witnessed":[7],"an":[8],"unprecedented":[9],"production":[10],"of":[11,28,79,114,121,132,137,165,186,194,210,226,245],"data":[12,73,98,105,172,197],"worldwide":[13],"that":[14,118,161,203],"has":[15,24],"generated":[16],"a":[17,42,149,155,199,207,223,234],"growing":[18],"demand":[19],"for":[20],"computing":[21,29,47,60,93,134,151,159,215],"resources":[22],"and":[23,31,36,65,71,97,136,229],"stimulated":[25],"design":[27],"paradigms":[30],"software":[32,224],"tools":[33],"to":[34,140],"efficiently":[35],"quickly":[37],"obtain":[38,119],"insights":[39],"on":[40,233],"such":[41,49],"Big":[43],"Data.":[44],"State-of-the-art":[45],"parallel":[46],"techniques":[48,84],"as":[50,129],"MapReduce":[52,116],"guarantee":[53],"high":[54],"performance":[55],"in":[56,88,125,153,176,198,241],"scenarios":[57,127],"where":[58,95],"involved":[59],"nodes":[61,96,133],"are":[62,74,99,239],"equally":[63],"sized":[64],"clustered":[66],"via":[67],"broadband":[68],"network":[69],"links,":[70],"co-located":[75],"with":[76],"cluster":[78],"nodes.":[80],"Unfortunately,":[81],"mentioned":[83],"proven":[86],"ineffective":[87],"geographically":[89,100],"distributed":[90,101],"scenarios,":[91],"i.e.,":[92],"contexts":[94],"across":[102],"multiple":[103],"distant":[104],"centers.":[106],"literature,":[109],"researchers":[110],"proposed":[112],"variants":[113],"paradigm":[117],"awareness":[120],"constraints":[123],"imposed":[124],"those":[126],"(such":[128],"imbalance":[131],"power":[135],"interconnecting":[138],"links)":[139],"enforce":[141],"smart":[142,200],"task":[143],"scheduling":[144],"strategies.":[145],"We":[146],"designed":[148],"hierarchical":[150],"framework":[152,169,228],"which":[154],"context-aware":[156],"scheduler":[157,205],"orchestrates":[158],"tasks":[160],"leverage":[162],"potential":[164],"vanilla":[167],"Hadoop":[168],"within":[170],"each":[171],"center":[173],"taking":[174],"part":[175,244],"computation.":[178],"this":[180],"work,":[181],"after":[182],"presenting":[183],"features":[185],"developed":[188],"framework,":[189],"advocate":[191],"opportunity":[193],"fragmenting":[195],"way":[201],"so":[202],"produces":[206],"fairer":[208],"distribution":[209],"workload":[212],"among":[213],"tasks.":[216],"To":[217],"prove":[218],"concept,":[220],"implemented":[222],"prototype":[225],"ran":[230],"several":[231],"experiments":[232],"small-scale":[235],"testbed.":[236],"Test":[237],"results":[238],"discussed":[240],"last":[243],"paper.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-01-26T00:00:00"}
