Results 201 to 210 of about 9,135 (230)
Tall and Skinny QR factorizations in MapReduce architectures.
, 2011 David F. Gleich, Paul G. Constantine
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MARIANE: MApReduce Implementation Adapted for HPC Environments
, 2011 Zacharia Fadika +3 more
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A Distributed VMD-BiLSTM Model for Taxi Demand Forecasting with GPS Sensor Data. [PDF]
Sensors (Basel)Naji HAH, Xue Q, Li T.
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Secure Computing for Fog-Enabled Industrial IoT. [PDF]
Sensors (Basel)Alvi AN +5 more
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Ordonnancement dynamique des transferts dans MapReduce sous contrainte de bande passante
, 2013 Sylvain Gault
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Tuple MapReduce: Beyond Classic MapReduce
2012 IEEE 12th International Conference on Data Mining, 2012This paper proposes Tuple Map Reduce, a new foundational model extending Map Reduce with the notion of tuples. Tuple Map Reduce allows to bridge the gap between the low-level constructs provided by Map Reduce and higher-level needs required by programmers, such as compound records, sorting or joins.
Eric Palacios +4 more
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An Advanced MapReduce: Cloud MapReduce, Enhancements and Applications
IEEE Transactions on Network and Service Management, 2014Recently, Cloud Computing is attracting great attention due to its provision of configurable computing resources. MapReduce (MR) is a popular framework for data-intensive distributed computing of batch jobs. MapReduce suffers from the following drawbacks: 1. It is sequential in its processing of Map and Reduce Phases 2.
Athanasios V. Vasilakos +7 more
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Secure Intersection with MapReduce
Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, 2019Relation intersection is a fundamental problem, which becomes non-trivial when the relations to be intersected are too large to fit on a single machine. Hence, a natural approach is to design parallel algorithms that are executed on a cluster of machines rented from a public cloud provider.
Ciucanu, Radu +3 more
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2017 International Conference on High Performance Computing & Simulation (HPCS), 2017
Integrity constraints (ICs) such as Functional Dependencies (FDs) or Inclusion Dependencies (INDs) are commonly used in databases to check if input relations obey to certain pre-defined quality metrics. While Data-Intensive Scalable Computing (DISC) platforms such as MapReduce commonly accept as input (semi-structured) data not in relational format ...
Interlandi, Matteo +3 more
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Integrity constraints (ICs) such as Functional Dependencies (FDs) or Inclusion Dependencies (INDs) are commonly used in databases to check if input relations obey to certain pre-defined quality metrics. While Data-Intensive Scalable Computing (DISC) platforms such as MapReduce commonly accept as input (semi-structured) data not in relational format ...
Interlandi, Matteo +3 more
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Cross-MapReduce: Data transfer reduction in geo-distributed MapReduce
Future Generation Computer Systems, 2021Abstract The MapReduce model is widely used to store and process big data in a distributed manner. MapReduce was originally developed for a single tightly coupled cluster of computers. Approaches such as Hierarchical and Geo-Hadoop are designed to address geo-distributed MapReduce processing.
Seyed Saeed Mirpour Marzuni +3 more
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