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Improving MapReduce energy efficiency for computation intensive workloads
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Outgoing claims: the papers this work cites, builds on, or argues with.
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The Case for Power Management in Web Servers
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Towards Efficient MapReduce Using MPI
inferredcites →https://doi.org/10.1093/bioinformatics/btp236openalex-snapshot
CloudBurst: highly sensitive read mapping with MapReduce
inferredcites →https://doi.org/10.1109/cloud.2011.68openalex-snapshot
Exploiting Spatio-temporal Tradeoffs for Energy-Aware MapReduce in the Cloud
inferredcites →https://doi.org/10.1109/hpca.2007.346181openalex-snapshot
Evaluating MapReduce for Multi-core and Multiprocessor Systems
inferredcites →https://doi.org/10.1109/icpp.2007.29openalex-snapshot
CPU MISER: A Performance-Directed, Run-Time System for Power-Aware 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/mc.2007.443openalex-snapshot
The Case for Energy-Proportional Computing
inferredcites →https://doi.org/10.1109/sc.2005.57openalex-snapshot
Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters
inferredcites →https://doi.org/10.1109/tpds.2009.76openalex-snapshot
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications
inferredcites →https://doi.org/10.1145/1740390.1740405openalex-snapshot
On the energy (in)efficiency of Hadoop clusters
inferredcites →https://doi.org/10.1145/1851290.1851296openalex-snapshot
To compress or not to compress - compute vs. IO tradeoffs for mapreduce energy efficiency
inferredcites →https://doi.org/10.1145/1851476.1851599openalex-snapshot
Parallelizing multiple group-by query in share-nothing environment
inferredcites →https://doi.org/10.14778/1920841.1920862openalex-snapshot
Energy management for MapReduce clusters
inferredcites →https://doi.org/10.15368/theses.2010.77openalex-snapshot
Reducing Cluster Power Consumption by Dynamically Suspending Idle Nodes
inferredcites →https://doi.org/10.2172/929723openalex-snapshot
Report to Congress on Server and Data Center Energy Efficiency: Public Law 109-431
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/spe.2599openalex-snapshot
Optimizing MapReduce for energy efficiency
inferred← citeshttps://doi.org/10.1007/978-3-030-24265-7_21openalex-snapshot
Trade-off Between Energy Consumption and Makespan in the Mapreduce Resource Allocation Problem
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Toward Green Data Lake Management and Analysis Through a CTMC Model
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Energy Efficient Scheduling of MapReduce Jobs
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Towards Efficient Power Management in MapReduce: Investigation of CPU-Frequencies Scaling on Power Efficiency in Hadoop
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Energy Saving Techniques for Cloud Data Centres: An Empirical Research Analysis
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Study on energy-consumption regularities of cloud computing systems by a novel evaluation model
inferred← citeshttps://doi.org/10.1007/s10586-013-0270-yopenalex-snapshot
MapReduce framework energy adaptation via temperature awareness
inferred← citeshttps://doi.org/10.1007/s10586-017-0893-5openalex-snapshot
Energy-efficient and QoS-aware model based resource consolidation in cloud data centers
inferred← citeshttps://doi.org/10.1007/s10586-017-1044-8openalex-snapshot
AEGEUS++: an energy-aware online partition skew mitigation algorithm for mapreduce in cloud
inferred← citeshttps://doi.org/10.1007/s10586-020-03146-7openalex-snapshot
A heuristic method towards deadline-aware energy-efficient mapreduce scheduling problem in Hadoop YARN
inferred← citeshttps://doi.org/10.1007/s10619-023-07436-yopenalex-snapshot
SimCost: cost-effective resource provision prediction and recommendation for spark workloads
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MapReduce: Review and open challenges
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SLA-aware energy-efficient scheduling scheme for Hadoop YARN
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Energy efficiency of VM consolidation in IaaS clouds
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Design and energy-efficient resource management of virtualized networked Fog architectures for the real-time support of IoT applications
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Marcher: A Heterogeneous System Supporting Energy-Aware High Performance Computing and Big Data Analytics
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2015.11.021openalex-snapshot
Analysis and evaluation of MapReduce solutions on an HPC cluster
inferred← citeshttps://doi.org/10.1016/j.future.2015.01.005openalex-snapshot
Governing energy consumption in Hadoop through CPU frequency scaling: An analysis
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/10.1016/j.jnca.2014.10.008openalex-snapshot
Energy-efficient algorithms for distributed storage system based on block storage structure reconfiguration
inferred← citeshttps://doi.org/10.1016/j.jpdc.2015.01.001openalex-snapshot
Performance and energy efficiency of big data applications in cloud environments: A Hadoop case study
inferred← citeshttps://doi.org/10.1016/j.procs.2014.05.006openalex-snapshot
An Empirical Study of Hadoop's Energy Efficiency on a HPC Cluster
inferred← citeshttps://doi.org/10.1016/j.suscom.2021.100530openalex-snapshot
PortAuthority: Integrating energy efficiency analysis into cross-platform development cycles via dynamic program analysis
inferred← citeshttps://doi.org/10.1049/iet-opt.2016.0165openalex-snapshot
Greening big data networks: velocity impact
inferred← citeshttps://doi.org/10.1109/access.2019.2907018openalex-snapshot
An Energy Efficiency Optimization and Control Model for Hadoop Clusters
inferred← citeshttps://doi.org/10.1109/apnoms.2012.6356077openalex-snapshot
A dynamic resource allocation method in IaaS based on deadline time
inferred← citeshttps://doi.org/10.1109/bigdata.2013.6691564openalex-snapshot
On the performance and energy efficiency of Hadoop deployment models
inferred← citeshttps://doi.org/10.1109/bigdata.congress.2014.15openalex-snapshot
Energy-Aware Scheduling of MapReduce Jobs
inferred← citeshttps://doi.org/10.1109/cgc.2012.59openalex-snapshot
Energy Efficient Computing through Productivity-Aware Frequency Scaling
inferred← citeshttps://doi.org/10.1109/cit.2016.42openalex-snapshot
Energy Aware Resource Management for MapReduce Jobs with Service Level Agreements in Cloud Data Centers
inferred← citeshttps://doi.org/10.1109/cloud.2012.137openalex-snapshot
Configuring a MapReduce Framework for Dynamic and Efficient Energy Adaptation
inferred← citeshttps://doi.org/10.1109/cloudcom.2016.0041openalex-snapshot
A Configurable Energy Aware Resource Management Technique for Optimization of Performance and Energy Consumption on Clouds
inferred← citeshttps://doi.org/10.1109/dasc.2011.111openalex-snapshot
A Power-Aware Scheduling of MapReduce Applications in the Cloud
inferred← citeshttps://doi.org/10.1109/discover47552.2019.9007941openalex-snapshot
Empirical Analysis of MapReduce Job Scheduling with respect to Energy Consumption of Clusters
inferred← citeshttps://doi.org/10.1109/dsdis.2015.45openalex-snapshot
On Understanding the Energy Impact of Speculative Execution in Hadoop
inferred← citeshttps://doi.org/10.1109/hpcc-css-icess.2015.181openalex-snapshot
SLA-Aware Energy-Efficient Scheduling Scheme for Hadoop YARN
inferred← citeshttps://doi.org/10.1109/hpcc.2014.33openalex-snapshot
An Energy-Efficient VM Placement in Cloud Datacenter
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/iccac.2014.36openalex-snapshot
Autonomic Workload and Resources Management of Cloud Computing Services
inferred← citeshttps://doi.org/10.1109/icpads.2016.0135openalex-snapshot
CPU Frequency Tuning to Improve Energy Efficiency of MapReduce Systems
inferred← citeshttps://doi.org/10.1109/icppw.2012.38openalex-snapshot
eTune: A Power Analysis Framework for Data-Intensive Computing
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A resource scheduling algorithm of cloud computing based on energy efficient optimization methods
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Power and energy characteristics of MapReduce data movements
inferred← citeshttps://doi.org/10.1109/ipdpsw.2016.86openalex-snapshot
Identification of critical parameters for MapReduce energy efficiency using statistical Design of Experiments
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Parallel Processing Systems for Big Data: A Survey
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How Processor Speedups Can Slow Down I/O Performance
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Execution Drafting: Energy Efficiency through Computation Deduplication
inferred← citeshttps://doi.org/10.1109/spices.2015.7091470openalex-snapshot
Analysis of MapReduce scheduling and its improvements in cloud environment
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Thermal-Aware and DVFS-Enabled Big Data Task Scheduling for Data Centers
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Energy-Aware Scheduling of MapReduce Jobs for Big Data Applications
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Energy-Efficient Task Scheduling for CPU-Intensive Streaming Jobs on Hadoop
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Energy Utilization Task Scheduling for MapReduce in Heterogeneous Clusters
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A Survey on Modeling Energy Consumption of Cloud Applications: Deconstruction, State of the Art, and Trade-Off Debates
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Improving Energy Efficiency of IO-Intensive MapReduce Jobs
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On Energyaware Allocation and Execution for Batch and Interactive MapReduce
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A Constraint Programming Based Energy Aware Resource Management Middleware for Clouds Processing MapReduce Jobs with Deadlines
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Understanding Behavior Trends of Big Data Frameworks in Ongoing Software-Defined Cyber-Infrastructure
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Reducing Energy Bloat in Large Model Training
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Towards Reducing Energy Consumption in Big Data Networks Using Fused Linear Programming
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Proactive Power and Thermal Aware Optimizations for Energy-Efficient Cloud Computing
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Energy Aware Resource Management for MapReduce Jobs
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Resource Management Techniques for Multi-Stage Jobs with Deadlines Running on Clouds
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SAGS: A SLA-Aware Green Scheduling in Heterogeneous Cloud Using Hadoop YARN
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Performance Optimization System for Hadoop and Spark Frameworks
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A systematic literature review on MapReduce scheduling methods
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Fog over Virtualized IoT: New Opportunity for Context-Aware Networked Applications and a Case Study
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Energy-Aware Cluster Reconfiguration Algorithm for the Big Data Analytics Platform Spark
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Uma análise do consumo de energia de ambientes de processamento de dados massivos em nuvem
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Performance and Energy Optimization on Terasort Algorithm by Task Self-Resizing
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