On the public citation graph
TomusBlobs: Towards Communication-Efficient Storage for MapReduce Applications in Azure
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-7908-2604-3_9openalex-snapshot
Imaging Genetics: Bio-Informatics and Bio-Statistics Challenges
inferredcites →https://doi.org/10.1016/j.jpdc.2010.08.004openalex-snapshot
BlobSeer: Next-generation data management for large scale infrastructures
inferredcites →https://doi.org/10.1109/cloudcom.2010.107openalex-snapshot
MapReduce in the Clouds for Science
inferredcites →https://doi.org/10.1109/ipdps.2010.5470433openalex-snapshot
BlobSeer: Bringing high throughput under heavy concurrency to Hadoop Map-Reduce applications
inferredcites →https://doi.org/10.1109/ipdps.2011.255openalex-snapshot
The Gfarm File System on Compute Clouds
inferredcites →https://doi.org/10.1109/sc.2010.17openalex-snapshot
Data Sharing Options for Scientific Workflows on Amazon EC2
inferredcites →https://doi.org/10.1145/1851476.1851532openalex-snapshot
Early observations on the performance of Windows Azure
inferredcites →https://doi.org/10.1145/1851476.1851535openalex-snapshot
Case study for running HPC applications in public clouds
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.3034openalex-snapshot
TomusBlobs: scalable data‐intensive processing on Azure clouds
inferred← citeshttps://doi.org/10.1007/978-1-4939-1905-5_14openalex-snapshot
Big Data Storage and Processing on Azure Clouds: Experiments at Scale and Lessons Learned
inferred← citeshttps://doi.org/10.1007/s10922-014-9307-7openalex-snapshot
Resource Management in Clouds: Survey and Research Challenges
inferred← citeshttps://doi.org/10.1016/j.future.2012.09.003openalex-snapshot
Monte Carlo simulation on heterogeneous distributed systems: A computing framework with parallel merging and checkpointing strategies
inferred← citeshttps://doi.org/10.1109/cluster.2016.22openalex-snapshot
Spark Versus Flink: Understanding Performance in Big Data Analytics Frameworks
inferred← citeshttps://doi.org/10.1504/ijcc.2013.055265openalex-snapshot
Scalable data management for map-reduce-based data-intensive applications: a view for cloud and hybrid infrastructures
inferred← citeshttps://doi.org/10.2200/s00915ed1v01y201904dtm060openalex-snapshot
Data-Intensive Workflow Management: For Clouds and Data-Intensive and Scalable Computing Environments
inferred← citeshttps://doi.org/10.70675/44b8eacdz7a7bz4db0z92c4zf4c61fc0186bopenalex-snapshot
Efficient Big Data Processing on Large-Scale Shared Platforms ˸ managing I/Os and Failure
inferred← citeshttps://doi.org/10.70675/fa20cd1az1980z4119zb8dcz11d06ae9a249openalex-snapshot
KerA : A Unified Ingestion and Storage System for Scalable Big Data Processing
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