Big Data Analysis: Methodologies, Frameworks and Real-World Applications
| dc.contributor.author | Branda, Francesco | |
| dc.contributor.author | Fortino, Giancarlo | |
| dc.contributor.author | Talia, Domenico | |
| dc.date.accessioned | 2025-11-28T08:57:15Z | |
| dc.date.issued | 2023-06-28 | |
| dc.description | Università della Calabria. Corso di laurea in Ingegneria Informatica, Modellistica, Elettronica e Sistemistica (DIMES). Dottorato di ricerca in Information and Communication Technologies (ICT). Ciclo XXXV | |
| dc.description.abstract | Inthelastyears,thecapacitytoproduceandcollectdatahasincreasedexpo- nentially.Thehugeamountofdatagenerated,commonlyreferredtoasBigData, thespeedatwhichitisproduced,anditsheterogeneityintermsofformatrepresent a challengetocurrentstorage,processing,andanalysiscapabilities.Thisscenario requiresthedesignandimplementationofnewarchitecturesandanalyticalplatform solutionsthatmustprocessBigDatatoextractcomplexpredictiveanddescriptive models.Today,high-performancecomputing(HPC)infrastructuressuchashighly parallelclusters,supercomputers,andcloudscanbeusedforprocessingandanalyz- ingmassivesourcesofreal-worlddatainvariousfields,includinggenomicsequencing andmedicalresearch,frauddetection,andweatherforecasting.Followingthesepre- liminaryobservations,thegoalofthisthesisistwofold.First,themainchallengesto besolvedforimplementinginnovativedataanalysisapplicationsonHPCsystemsare investigated.Inparticular,themainkeyresearchtopicsaddressedinclude:(i)stud- iesofsoftwaresystemsforBigDatastoring,processing,andanalysis;(ii)methods, techniques,andprototypesdesignedandusedtoimplementBigDatasolutionson massivedatasourcesrequiringtheuseofhigh-performancecomputingsystems;and (iii)designandprogrammingissuesforBigDataanalysisinExascalesystems,which willrepresentthenextcomputingstep.Second,severalinnovativeapplicationsand usecasesofBigDataanalyticsthatcanbeimplementedinlarge-scaleparallelsys- temsareproposed.Theseresearchcontributionsprovidenewinsightsandsolutions forextractingusefulknowledgefromlargevolumesofdata,describingmethodsand mechanismstosupportusers,practitioners,andscientistsworkingintheareaofBig Datainthedesignandexecutionofdataanalysistechniquesindifferentapplication domains. | |
| dc.identifier.uri | http://hdl.handle.net/10955/5683 | |
| dc.language.iso | en | |
| dc.publisher | Università della Calabria | |
| dc.subject | big data analysis | |
| dc.subject | high-performance computing (HPC) | |
| dc.subject | social data mining | |
| dc.subject | machine learning | |
| dc.subject | infectious diseases modelling | |
| dc.title | Big Data Analysis: Methodologies, Frameworks and Real-World Applications | |
| dc.type | Thesis |