KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
SRI-Center for Numerical Porous Media
Permanent link to this recordhttp://hdl.handle.net/10754/556722
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AbstractThe OpenDBDDAS Toolkit is a software framework to provide support for more easily creating and expanding dynamic big data-driven application systems (DBDDAS) that are common in environmental systems, many engineering applications, disaster management, traffic management, and manufacturing. In this paper, we describe key features needed to implement a secure MapReduce and Hadoop-like system for high performance clusters that guarantees a certain level of privacy of data from other concurrent users of the system. We also provide examples of a secure MapReduce prototype and compare it to another high performance MapReduce, MR-MPI.
CitationOpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems 2015, 51:1675 Procedia Computer Science
JournalProcedia Computer Science
Conference/Event nameInternational Conference on Computational Science, ICCS 2002