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Optimizing Power and Performance Trade-offs of MapReduce Job Processing with Heterogeneous Multi-core Processors

https://doi.org/10.1109/cloud.2014.41
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1109/cloud.2013.107openalex-snapshot
Performance Modeling of MapReduce Jobs in Heterogeneous Cloud Environments
inferredcites →https://doi.org/10.1109/cluster.2011.36openalex-snapshot
Play It Again, SimMR!
inferredcites →https://doi.org/10.1109/icpp.2010.73openalex-snapshot
Performance Management of Accelerated MapReduce Workloads in Heterogeneous Clusters
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/noms.2012.6212006openalex-snapshot
Deadline-based workload management for MapReduce environments: Pieces of the performance puzzle
inferredcites →https://doi.org/10.1109/noms.2014.6838339openalex-snapshot
Heterogeneous cores for MapReduce processing: Opportunity or challenge?
inferredcites →https://doi.org/10.1145/1327452.1327492openalex-snapshot
MapReduce
inferredcites →https://doi.org/10.1145/1454115.1454128openalex-snapshot
The PARSEC benchmark suite
inferredcites →https://doi.org/10.1145/1755913.1755940openalex-snapshot
Delay scheduling
inferredcites →https://doi.org/10.1145/1998582.1998637openalex-snapshot
ARIA
inferredcites →https://doi.org/10.1145/2150976.2150984openalex-snapshot
Tarazu
inferredcites →https://doi.org/10.1145/2209249.2209272openalex-snapshot
Looking back and looking forward
inferredcites →https://doi.org/10.1145/2391229.2391233openalex-snapshot
Sailfish
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/10.1007/978-3-319-49583-5_48openalex-snapshot
D-SPACE4Cloud: A Design Tool for Big Data Applications
inferred← citeshttps://doi.org/10.1007/s11227-018-2426-2openalex-snapshot
An optimization framework for the capacity allocation and admission control of MapReduce jobs in cloud systems
inferred← citeshttps://doi.org/10.1016/j.future.2016.12.034openalex-snapshot
Mixed integer linear programming for quality of service optimization in Clouds
inferred← citeshttps://doi.org/10.1016/j.future.2017.11.010openalex-snapshot
Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights
inferred← citeshttps://doi.org/10.1109/icac.2015.30openalex-snapshot
Optimizing Energy, Locality and Priority in a MapReduce Cluster
inferred← citeshttps://doi.org/10.1109/noms.2016.7502934openalex-snapshot
Workload interleaving with performance guarantees in data centers
inferred← citeshttps://doi.org/10.1109/tbdata.2016.2607756openalex-snapshot
The Memory Challenge in Reduce Phase of MapReduce Applications
inferred← citeshttps://doi.org/10.1109/tcc.2015.2415772openalex-snapshot
DyScale: A MapReduce Job Scheduler for Heterogeneous Multicore Processors
inferred← citeshttps://doi.org/10.1109/tcc.2017.2677906openalex-snapshot
Faster MapReduce Computation on Clouds Through Better Performance Estimation
inferred← citeshttps://doi.org/10.1109/tcc.2019.2926254openalex-snapshot
Profit Maximization of Big Data Jobs in Cloud Using Stochastic Optimization
inferred← citeshttps://doi.org/10.21220/s2z59wopenalex-snapshot
Workload Interleaving With Performance Guarantees In Data Centers
inferred← citeshttps://doi.org/10.32628/cseit172568openalex-snapshot
Splitting and Grouping of Jobs in Map Reduction for Various Multicore Processors
inferred← citeshttps://doi.org/10.5281/zenodo.21733598openalex-snapshot
Various Multicore Processors with Splitting and Federation of Jobs In Map Reduction
inferred← citeshttps://doi.org/10.70675/e8bdff5bz844ez4473zbf9ez36d0232b71acopenalex-snapshot
Optimisation de la gestion des ressources sur une plate-forme informatique du type Big Data basée sur le logiciel Hadoop
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