000865715 001__ 865715
000865715 005__ 20210130003127.0
000865715 0247_ $$2Handle$$a2128/23964
000865715 037__ $$aFZJ-2019-05050
000865715 041__ $$aEnglish
000865715 1001_ $$0P:(DE-Juel1)132190$$aMemon, Mohammad Shahbaz$$b0$$eCorresponding author
000865715 245__ $$aStandards-based Models and Architectures to Automate Scalable and Distributed Data Processing and Analysis$$f - 2019-10-04
000865715 260__ $$c2019
000865715 300__ $$a102 pp.
000865715 3367_ $$2DataCite$$aOutput Types/Dissertation
000865715 3367_ $$2ORCID$$aDISSERTATION
000865715 3367_ $$2BibTeX$$aPHDTHESIS
000865715 3367_ $$02$$2EndNote$$aThesis
000865715 3367_ $$0PUB:(DE-HGF)11$$2PUB:(DE-HGF)$$aDissertation / PhD Thesis$$bphd$$mphd$$s1579675342_9791
000865715 3367_ $$2DRIVER$$adoctoralThesis
000865715 502__ $$aDissertation, University of Iceland, 2019$$bDissertation$$cUniversity of Iceland$$d2019
000865715 520__ $$aScientific communities engaging in big data analysis face numerous challenges in managing complex computations and the related data on emerging and distributed computing infrastructures. Large-scale data analysis requires applications with simplified access to multiple resource management systems. Several generic or domain-specific technologies have been developed to exploit diversified computing environments, but due to the heterogeneity of computing and data architectures they are not capable of enabling real science cases. Scientific gateways and workflows are one such example which requires the management of jobs on multiple kinds of batch systems using heterogeneous supercomputing architectures and access to advanced distributed file systems. To support these requirements, a unified architectural framework is presented in this dissertation that coalesces the right combination of standards and adequate middleware realisation. This framework manages concurrent access for diversified user communities through consistent and robust computing and data interfaces oriented to current application and infrastructure demands. The investigations reported in this dissertation were mainly motivated by physical and machine-learning models, represented by two scientific case studies: biophysics and Earth sciences. In the field of biophysics, the UltraScan scientific gateway is enhanced to enable the processing of domain-specific data through standards-based job and data management interfaces in HPC environments. The second domain deals with Earth sciences and automates the processing of machine-learning algorithms (e.g. classification of remote sensing images) using scalable and parallel implementations. As proof of concept, both the case studies are supported through open source implementations, in the form of middleware realisation, client APIs and their integration with state-of-the-art science gateway frameworks.
000865715 536__ $$0G:(DE-HGF)POF3-512$$a512 - Data-Intensive Science and Federated Computing (POF3-512)$$cPOF3-512$$fPOF III$$x0
000865715 8564_ $$uhttps://opinvisindi.is/handle/20.500.11815/1299
000865715 8564_ $$uhttps://juser.fz-juelich.de/record/865715/files/uiphdthesis_shahbaz_memon20190906_final_for_printing_papers_upscaled_p88_corrected.pdf$$yOpenAccess
000865715 8564_ $$uhttps://juser.fz-juelich.de/record/865715/files/uiphdthesis_shahbaz_memon20190906_final_for_printing_papers_upscaled_p88_corrected.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000865715 909CO $$ooai:juser.fz-juelich.de:865715$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000865715 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132190$$aForschungszentrum Jülich$$b0$$kFZJ
000865715 9131_ $$0G:(DE-HGF)POF3-512$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vData-Intensive Science and Federated Computing$$x0
000865715 9141_ $$y2019
000865715 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000865715 920__ $$lyes
000865715 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
000865715 980__ $$aphd
000865715 980__ $$aVDB
000865715 980__ $$aUNRESTRICTED
000865715 980__ $$aI:(DE-Juel1)JSC-20090406
000865715 9801_ $$aFullTexts