On the public citation graph
Configuring a MapReduce Framework for Dynamic and Efficient Energy Adaptation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.jpdc.2005.04.019openalex-snapshot
A framework for reliable and efficient data placement in distributed computing systems
inferredcites →https://doi.org/10.1093/bioinformatics/btp236openalex-snapshot
CloudBurst: highly sensitive read mapping with MapReduce
inferredcites →https://doi.org/10.1109/ccgrid.2012.135openalex-snapshot
MARLA: MapReduce for Heterogeneous Clusters
inferredcites →https://doi.org/10.1109/grid.2011.20openalex-snapshot
MARIANE: MApReduce Implementation Adapted for HPC Environments
inferredcites →https://doi.org/10.1109/igcc.2011.6008564openalex-snapshot
Improving MapReduce energy efficiency for computation intensive workloads
inferredcites →https://doi.org/10.1109/ipdps.2007.370559openalex-snapshot
An Energy-Efficient Framework for Large-Scale Parallel Storage Systems
inferredcites →https://doi.org/10.1109/ipdpsw.2010.5470880openalex-snapshot
Improving MapReduce performance through data placement in heterogeneous Hadoop clusters
inferredcites →https://doi.org/10.1109/mc.2007.443openalex-snapshot
The Case for Energy-Proportional Computing
inferredcites →https://doi.org/10.1145/1740390.1740405openalex-snapshot
On the energy (in)efficiency of Hadoop clusters
inferredcites →https://doi.org/10.14778/1920841.1920862openalex-snapshot
Energy management for MapReduce clusters
inferredcites →https://doi.org/10.5555/1855741.1855744openalex-snapshot
Improving MapReduce performance in heterogeneous environments
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s11760-016-0964-8openalex-snapshot
Energy-aware processing of big data in homogeneous cluster
inferred← citeshttps://doi.org/10.1016/j.jpdc.2016.04.001openalex-snapshot
Towards efficient resource provisioning in MapReduce
inferred← citeshttps://doi.org/10.1080/17538947.2016.1239771openalex-snapshot
Big Data and cloud computing: innovation opportunities and challenges
inferred← citeshttps://doi.org/10.1109/cloud.2016.0077openalex-snapshot
Exploring the Design Space for Optimizations with Apache Aurora and Mesos
inferred← citeshttps://doi.org/10.1109/cloud.2017.41openalex-snapshot
Electron: Towards Efficient Resource Management on Heterogeneous Clusters with Apache Mesos
inferred← citeshttps://doi.org/10.1109/cloud.2018.00024openalex-snapshot
Analysis of Dynamically Switching Energy-Aware Scheduling Policies for Varying Workloads
inferred← citeshttps://doi.org/10.1109/igcc.2013.6604489openalex-snapshot
Power and energy characteristics of MapReduce data movements
inferred← citeshttps://doi.org/10.1109/wi-iat.2014.15openalex-snapshot
Big Data - Characterizing an Emerging Research Field Using Topic Models
inferred← citeshttps://doi.org/10.1109/wisa.2015.53openalex-snapshot
An Approach to Instantly Detecting Fake Plates Based on Large-Scale ANPR Data
inferred← citeshttps://doi.org/10.1145/2684464.2684484openalex-snapshot
Improving Energy Efficiency of IO-Intensive MapReduce Jobs
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