Scalable Distributed Virtual Data Structures
Jajodia, Sushil; Litwin, Witold; Schwarz, Thomas (2014), Scalable Distributed Virtual Data Structures, 2014 ASE BIGDATA/SOCIALCOM/CYBERSECURITY Conference, Academy of Science and Engineering : Greensboro, NC, USA
Type
Communication / ConférenceDate
2014Conference title
2014 ASE BIGDATA/SOCIALCOM/CYBERSECURITY ConferenceConference date
2014-05Conference city
StanfordConference country
United StatesBook title
2014 ASE BIGDATA/SOCIALCOM/CYBERSECURITY ConferencePublisher
Academy of Science and Engineering
Published in
Greensboro, NC, USA
ISBN
978-1-62561-000-3
Metadata
Show full item recordAuthor(s)
Jajodia, SushilInterdisciplinary Center for Economic Science, George Mason University
Litwin, Witold
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Schwarz, Thomas
Université d'Uruguay
Abstract (EN)
The MapReduce framework allows for distributed/parallel scans followed by aggregations of data in large stored files. We propose here scalable distributed structures conveying the MapReduce framework to virtual files. Virtual files are not stored, but materialize dynamically in cloud nodes bysome Big Computation. A major constraint on a virtual file is a client-defined reasonable bound on processing time at each node, e.g., 10 min. We define two schemes for virtual files called VH* and VR*. They provide scalable distributed hash and range partitioning respectively and respect a clientimposed time limit. We show their usefulness by applying them to the problem of key recovery and of solving the knapsack problem.Subjects / Keywords
MapReduceRelated items
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