Learning to Schedule: A Supervised Learning Framework for Network-Aware Scheduling of Data-Intensive Workloads
Fuente:
arXiv
Saved in:
| Main Authors: | Timilsina, Sankalpa, Shannigrahi, Susmit |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LIDC: A Location Independent Multi-Cluster Computing Framework for Data Intensive Science
by: Timilsina, Sankalpa, et al.
Published: (2025)
by: Timilsina, Sankalpa, et al.
Published: (2025)
PSMOA: Policy Support Multi-Objective Optimization Algorithm for Decentralized Data Replication
by: Wang, Xi, et al.
Published: (2025)
by: Wang, Xi, et al.
Published: (2025)
Scheduling Data-Intensive Workloads in Large-Scale Distributed Systems: Trends and Challenges
by: Stavrinides, Georgios L., et al.
Published: (2025)
by: Stavrinides, Georgios L., et al.
Published: (2025)
MDTP -- An Adaptive Multi-Source Data Transfer Protocol
by: Abdollah, Sepideh, et al.
Published: (2025)
by: Abdollah, Sepideh, et al.
Published: (2025)
LLMSched: Uncertainty-Aware Workload Scheduling for Compound LLM Applications
by: Zhu, Botao, et al.
Published: (2025)
by: Zhu, Botao, et al.
Published: (2025)
Eventually-Consistent Federated Scheduling for Data Center Workloads
by: Thiyyakat, Meghana, et al.
Published: (2023)
by: Thiyyakat, Meghana, et al.
Published: (2023)
PAL: A Variability-Aware Policy for Scheduling ML Workloads in GPU Clusters
by: Jain, Rutwik, et al.
Published: (2024)
by: Jain, Rutwik, et al.
Published: (2024)
Sustainable Graph Analytics Workload Scheduling with Evolutionary Reinforcement Learning in Edge-Cloud Systems
by: Ramicetty, P., et al.
Published: (2026)
by: Ramicetty, P., et al.
Published: (2026)
An Online Fragmentation-Aware Scheduler for Managing GPU-Sharing Workloads on Multi-Instance GPUs
by: Ting, Hsu-Tzu, et al.
Published: (2025)
by: Ting, Hsu-Tzu, et al.
Published: (2025)
Duration-Informed Workload Scheduler
by: Loreti, Daniela, et al.
Published: (2026)
by: Loreti, Daniela, et al.
Published: (2026)
Quantifying the Carbon Reduction of DAG Workloads: A Job Shop Scheduling Perspective
by: Bostandoost, Roozbeh, et al.
Published: (2025)
by: Bostandoost, Roozbeh, et al.
Published: (2025)
Efficient Data Labeling and Optimal Device Scheduling in HWNs Using Clustered Federated Semi-Supervised Learning
by: Hamood, Moqbel, et al.
Published: (2024)
by: Hamood, Moqbel, et al.
Published: (2024)
Workload Schedulers -- Genesis, Algorithms and Differences
by: Sliwko, Leszek, et al.
Published: (2025)
by: Sliwko, Leszek, et al.
Published: (2025)
Evaluating Malleable Job Scheduling in HPC Clusters using Real-World Workloads
by: Zojer, Patrick, et al.
Published: (2026)
by: Zojer, Patrick, et al.
Published: (2026)
A Review of Tools and Techniques for Optimization of Workload Mapping and Scheduling in Heterogeneous HPC System
by: Sharma, Aasish Kumar, et al.
Published: (2025)
by: Sharma, Aasish Kumar, et al.
Published: (2025)
Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters
by: Luo, Ziyue, et al.
Published: (2025)
by: Luo, Ziyue, et al.
Published: (2025)
Workflow-Driven Modeling for the Compute Continuum: An Optimization Approach to Automated System and Workload Scheduling
by: Sharma, Aasish Kumar, et al.
Published: (2025)
by: Sharma, Aasish Kumar, et al.
Published: (2025)
Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey
by: Liang, Feng, et al.
Published: (2024)
by: Liang, Feng, et al.
Published: (2024)
Priority-Aware Preemptive Scheduling for Mixed-Priority Workloads in MoE Inference
by: Siavashi, Mohammad, et al.
Published: (2025)
by: Siavashi, Mohammad, et al.
Published: (2025)
A HPC Co-Scheduler with Reinforcement Learning
by: Souza, Abel, et al.
Published: (2024)
by: Souza, Abel, et al.
Published: (2024)
Collaborative Resource Management and Workloads Scheduling in Cloud-Assisted Mobile Edge Computing across Timescales
by: Tang, Lujie, et al.
Published: (2024)
by: Tang, Lujie, et al.
Published: (2024)
Data-Locality-Aware Task Assignment and Scheduling for Distributed Job Executions
by: Zhao, Hailiang, et al.
Published: (2024)
by: Zhao, Hailiang, et al.
Published: (2024)
A Taxonomy of Schedulers -- Operating Systems, Clusters and Big Data Frameworks
by: Sliwko, Leszek
Published: (2025)
by: Sliwko, Leszek
Published: (2025)
Metronome: Efficient Scheduling for Periodic Traffic Jobs with Network and Priority Awareness
by: Jiang, Hao, et al.
Published: (2025)
by: Jiang, Hao, et al.
Published: (2025)
Night-Window Batching versus Carbon-Aware Scheduling for Clinical AI GPU Workloads
by: Doshi, Nishi, et al.
Published: (2026)
by: Doshi, Nishi, et al.
Published: (2026)
An Advanced Reinforcement Learning Framework for Online Scheduling of Deferrable Workloads in Cloud Computing
by: Dong, Hang, et al.
Published: (2024)
by: Dong, Hang, et al.
Published: (2024)
SneakPeek: Data-Aware Model Selection and Scheduling for Inference Serving on the Edge
by: Wolfrath, Joel, et al.
Published: (2025)
by: Wolfrath, Joel, et al.
Published: (2025)
WOW: Workflow-Aware Data Movement and Task Scheduling for Dynamic Scientific Workflows
by: Lehmann, Fabian, et al.
Published: (2025)
by: Lehmann, Fabian, et al.
Published: (2025)
Trustworthy Scheduling for Big Data Applications
by: Tomaras, Dimitrios, et al.
Published: (2026)
by: Tomaras, Dimitrios, et al.
Published: (2026)
SLO-Aware Scheduling for Large Language Model Inferences
by: Huang, Jinqi, et al.
Published: (2025)
by: Huang, Jinqi, et al.
Published: (2025)
Carbon-Aware Mapping and Scheduling for Deadline-Constrained Workflows
by: Schweisgut, Dominik, et al.
Published: (2026)
by: Schweisgut, Dominik, et al.
Published: (2026)
Topology-aware Preemptive Scheduling for Co-located LLM Workloads
by: Zhang, Ping, et al.
Published: (2024)
by: Zhang, Ping, et al.
Published: (2024)
GrapheonRL: A Graph Neural Network and Reinforcement Learning Framework for Constraint and Data-Aware Workflow Mapping and Scheduling in Heterogeneous HPC Systems
by: Sharma, Aasish Kumar, et al.
Published: (2025)
by: Sharma, Aasish Kumar, et al.
Published: (2025)
Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling
by: Zhang, Xinyi, et al.
Published: (2024)
by: Zhang, Xinyi, et al.
Published: (2024)
DCSim: Computing and Networking Integration based Container Scheduling Simulator for Data Centers
by: Hu, Jinlong, et al.
Published: (2024)
by: Hu, Jinlong, et al.
Published: (2024)
EAT: QoS-Aware Edge-Collaborative AIGC Task Scheduling via Attention-Guided Diffusion Reinforcement Learning
by: Xu, Zhifei, et al.
Published: (2025)
by: Xu, Zhifei, et al.
Published: (2025)
A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
by: Wang, Zhiyu, et al.
Published: (2025)
by: Wang, Zhiyu, et al.
Published: (2025)
Carbon-Aware Workflow Scheduling with Fixed Mapping and Deadline Constraint
by: Schweisgut, Dominik, et al.
Published: (2025)
by: Schweisgut, Dominik, et al.
Published: (2025)
Cortex: Workflow-Aware Resource Pooling and Scheduling for Agentic Serving
by: Pagonas, Nikos, et al.
Published: (2025)
by: Pagonas, Nikos, et al.
Published: (2025)
FATE: Future-State-Aware Scheduling for Heterogeneous LLM Workflows
by: Huang, Zirui, et al.
Published: (2026)
by: Huang, Zirui, et al.
Published: (2026)
Similar Items
-
LIDC: A Location Independent Multi-Cluster Computing Framework for Data Intensive Science
by: Timilsina, Sankalpa, et al.
Published: (2025) -
PSMOA: Policy Support Multi-Objective Optimization Algorithm for Decentralized Data Replication
by: Wang, Xi, et al.
Published: (2025) -
Scheduling Data-Intensive Workloads in Large-Scale Distributed Systems: Trends and Challenges
by: Stavrinides, Georgios L., et al.
Published: (2025) -
MDTP -- An Adaptive Multi-Source Data Transfer Protocol
by: Abdollah, Sepideh, et al.
Published: (2025) -
LLMSched: Uncertainty-Aware Workload Scheduling for Compound LLM Applications
by: Zhu, Botao, et al.
Published: (2025)