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Data-Intensive Workload Consolidation for the Hadoop Distributed File System
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.2895openalex-snapshot
A study on using uncertain time series matching algorithms for MapReduce applications
inferredcites →https://doi.org/10.1109/icppw.2011.25openalex-snapshot
Energy-Aware Workload Consolidation on GPU
inferredcites →https://doi.org/10.1109/iiswc.2007.4362180openalex-snapshot
An Evaluation of Server Consolidation Workloads for Multi-Core Designs
inferredcites →https://doi.org/10.1109/ipdps.2011.98openalex-snapshot
Shared Resource Monitoring and Throughput Optimization in Cloud-Computing Datacenters
inferredcites →https://doi.org/10.1109/ispass.2010.5452065openalex-snapshot
Cache contention and application performance prediction for multi-core systems
inferredcites →https://doi.org/10.1109/mascots.2011.12openalex-snapshot
The Case for Evaluating MapReduce Performance Using Workload Suites
inferredcites →https://doi.org/10.1109/msst.2010.5496972openalex-snapshot
The Hadoop Distributed File System
inferredcites →https://doi.org/10.1109/noms.2010.5488494openalex-snapshot
Performance-driven task co-scheduling for MapReduce environments
inferredcites →https://doi.org/10.1109/tc.2011.141openalex-snapshot
Modeling Cache Contention and Throughput of Multiprogrammed Manycore Processors
inferredcites →https://doi.org/10.1145/1807128.1807136openalex-snapshot
Virtual machine power metering and provisioning
inferredcites →https://doi.org/10.14778/1920841.1920902openalex-snapshot
Runtime measurements in the cloud
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.6247openalex-snapshot
Enhancing disk input output performance in consolidated virtualized cloud platforms using a randomized approximation scheme
inferred← citeshttps://doi.org/10.1002/cpe.8260openalex-snapshot
An archive‐based method for efficiently handling small file problems in HDFS
inferred← citeshttps://doi.org/10.1007/978-3-030-69244-5_35openalex-snapshot
Graceful Performance Degradation in Apache Storm
inferred← citeshttps://doi.org/10.1007/s10586-016-0593-6openalex-snapshot
P-Aware: a proportional multi-resource scheduling strategy in cloud data center
inferred← citeshttps://doi.org/10.1016/j.cpc.2016.07.015openalex-snapshot
MaMR: High-performance MapReduce programming model for material cloud applications
inferred← citeshttps://doi.org/10.1016/j.future.2014.10.028openalex-snapshot
CloudFlow: A data-aware programming model for cloud workflow applications on modern HPC systems
inferred← citeshttps://doi.org/10.1109/ccgrid49817.2020.00-30openalex-snapshot
Q-Flink: A QoS-Aware Controller for Apache Flink
inferred← citeshttps://doi.org/10.1109/cloud49709.2020.00082openalex-snapshot
Spark-Tuner: An Elastic Auto-Tuner for Apache Spark Streaming
inferred← citeshttps://doi.org/10.1109/dasc-picom-datacom-cyberscitec.2016.37openalex-snapshot
A Proportional Multi-resource Scheduling Model in SDCloud
inferred← citeshttps://doi.org/10.1109/ictc.2014.6983331openalex-snapshot
TS-Hadoop: Handling access skew in MapReduce by using tiered storage infrastructure
inferred← citeshttps://doi.org/10.1109/macs.2018.8628336openalex-snapshot
An Investigation of Hadoop Parameters in SDN-enabled Clusters
inferred← citeshttps://doi.org/10.1109/nca51143.2020.9306697openalex-snapshot
A Dynamic Resource Controller for Resolving Quality of Service Issues in Modern Streaming Processing Engines
inferred← citeshttps://doi.org/10.1109/nca53618.2021.9685244openalex-snapshot
Data-Intensive Workload Consolidation in Serverless (Lambda/FaaS) Platforms
inferred← citeshttps://doi.org/10.1109/nca53618.2021.9685833openalex-snapshot
QSpark: Distributed Execution of Batch & Streaming Analytics in Spark Platform
inferred← citeshttps://doi.org/10.1109/nca61908.2024.00032openalex-snapshot
Controlling Performance Interference in Multi-Tenant Containerized Environments
inferred← citeshttps://doi.org/10.1109/pdcat46702.2019.00079openalex-snapshot
Disk Throughput Controller for Cloud Data-Centers
inferred← citeshttps://doi.org/10.1109/uic-atc-scalcom-cbdcom-iop.2015.51openalex-snapshot
Super Rack: Reusing the Results of Queries in MapReduce Systems
inferred← citeshttps://doi.org/10.1145/3386367.3431680openalex-snapshot
Auto-tuning of large-scale iterative operations on modern streaming platforms
inferred← citeshttps://doi.org/10.1371/journal.pone.0175861openalex-snapshot
Speeding up profiling program’s runtime characteristics for workload consolidation
inferred← citeshttps://doi.org/10.1587/transcom.2015itp0011openalex-snapshot
Reusing the Results of Queries in MapReduce Systems by Adopting Shared Storage
inferred← citeshttps://doi.org/10.26686/wgtn.17145944openalex-snapshot
Resource and Performance Modelling of Hadoop Clusters Using Machine Learning
inferred← citeshttps://doi.org/10.26686/wgtn.17145944.v1openalex-snapshot
Resource and Performance Modelling of Hadoop Clusters Using Machine Learning
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