On the public citation graph
Energy-Efficient Dynamic Scheduling of Deadline-Constrained MapReduce Workflows
0 signed · 32 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-84882-310-5openalex-snapshot
Scheduling for Parallel Processing
inferredcites →https://doi.org/10.1007/978-3-642-32820-6_18openalex-snapshot
Energy Efficient Frequency Scaling and Scheduling for Malleable Tasks
inferredcites →https://doi.org/10.1016/j.future.2015.01.005openalex-snapshot
Governing energy consumption in Hadoop through CPU frequency scaling: An analysis
inferredcites →https://doi.org/10.1016/j.future.2017.07.050openalex-snapshot
Energy-efficient mapping of large-scale workflows under deadline constraints in big data computing systems
inferredcites →https://doi.org/10.1016/j.ins.2015.02.023openalex-snapshot
Maximizing reliability with energy conservation for parallel task scheduling in a heterogeneous cluster
inferredcites →https://doi.org/10.1016/j.ins.2016.08.003openalex-snapshot
Bi-objective workflow scheduling of the energy consumption and reliability in heterogeneous computing systems
inferredcites →https://doi.org/10.1109/apscc.2008.189openalex-snapshot
Runtime Prediction Based Grid Scheduling of Parameter Sweep Jobs
inferredcites →https://doi.org/10.1109/icdcs.2015.44openalex-snapshot
Towards Energy Efficiency in Heterogeneous Hadoop Clusters by Adaptive Task Assignment
inferredcites →https://doi.org/10.1109/ipdps.2015.36openalex-snapshot
Resource and Deadline-Aware Job Scheduling in Dynamic Hadoop Clusters
inferredcites →https://doi.org/10.1109/tc.2012.120openalex-snapshot
Scheduling Precedence Constrained Tasks with Reduced Processor Energy on Multiprocessor Computers
inferredcites →https://doi.org/10.1109/tc.2012.166openalex-snapshot
Exploiting Spatio-Temporal Tradeoffs for Energy-Aware MapReduce in the Cloud
inferredcites →https://doi.org/10.1109/tcc.2015.2453966openalex-snapshot
EnReal: An Energy-Aware Resource Allocation Method for Scientific Workflow Executions in Cloud Environment
inferredcites →https://doi.org/10.1109/tpds.2010.208openalex-snapshot
Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions
inferredcites →https://doi.org/10.1109/tpds.2014.2358556openalex-snapshot
Energy-Aware Scheduling of MapReduce Jobs for Big Data Applications
inferredcites →https://doi.org/10.1109/tpds.2015.2405552openalex-snapshot
Hadoop Performance Modeling for Job Estimation and Resource Provisioning
inferredcites →https://doi.org/10.1109/tpds.2016.2542817openalex-snapshot
Minimum Dependencies Energy-Efficient Scheduling in Data Centers
inferredcites →https://doi.org/10.1145/1807128.1807164openalex-snapshot
Robust and flexible power-proportional storage
inferredcites →https://doi.org/10.1145/2168836.2168842openalex-snapshot
Energy efficiency for large-scale MapReduce workloads with significant interactive analysis
inferredcites →https://doi.org/10.1145/2814576.2814807openalex-snapshot
Improving Preemptive Scheduling with Application-Transparent Checkpointing in Shared Clusters
inferredcites →https://doi.org/10.1201/9781420010749openalex-snapshot
Handbook of Approximation Algorithms and Metaheuristics
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1089/big.2020.0081openalex-snapshot
MRS-DP: Improving Performance and Resource Utilization of Big Data Applications with Deadlines and Priorities
inferred← citeshttps://doi.org/10.1109/access.2024.3509218openalex-snapshot
Trends, Approaches, and Gaps in Scientific Workflow Scheduling: A Systematic Review
inferred← citeshttps://doi.org/10.1109/bdcloud.2018.00162openalex-snapshot
On Scheduling of High-Throughput Scientific Workflows under Budget Constraints in Multi-Cloud Environments
inferred← citeshttps://doi.org/10.1109/cluster52292.2023.00016openalex-snapshot
HIOS: Hierarchical Inter-Operator Scheduler for Real-Time Inference of DAG-Structured Deep Learning Models on Multiple GPUs
inferred← citeshttps://doi.org/10.1109/ipdps64566.2025.00069openalex-snapshot
PredTOP: Latency Predictor Utilizing DAG Transformers for Distributed Deep Learning Training with Operator Parallelism
inferred← citeshttps://doi.org/10.1109/mlhpc.2018.8638629openalex-snapshot
Scaling Deep Learning for Cancer with Advanced Workflow Storage Integration
inferred← citeshttps://doi.org/10.1109/scw63240.2024.00144openalex-snapshot
AM-DGCNN: Leveraging Graph Attention Networks and Edge Attributes for Link Classification in Knowledge Graphs
inferred← citeshttps://doi.org/10.1145/3437801.3441615openalex-snapshot
In-situ workflow auto-tuning through combining component models
inferred← citeshttps://doi.org/10.1145/3458817.3476197openalex-snapshot
Bootstrapping in-situ workflow auto-tuning via combining performance models of component applications
inferred← citeshttps://doi.org/10.2174/2666255816666230608165146openalex-snapshot
Performance Challenges and Solutions in Big Data Platform Hadoop
inferred← citeshttps://doi.org/10.3233/idt-190363openalex-snapshot
A systematic literature review on MapReduce scheduling methods
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.