ADAPT: A Self-Calibrating Proactive Autoscaler for Container Orchestration
Fuente:
arXiv
Saved in:
| Main Author: | Baghel, Himanshu Singh |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration
by: Hu, Zhengding, et al.
Published: (2026)
by: Hu, Zhengding, et al.
Published: (2026)
AAPA: An Archetype-Aware Predictive Autoscaler with Uncertainty Quantification for Serverless Workloads on Kubernetes
by: Zhang, Guilin, et al.
Published: (2025)
by: Zhang, Guilin, et al.
Published: (2025)
Quantifying Autoscaler Vulnerabilities: An Empirical Study of Resource Misallocation Induced by Cloud Infrastructure Faults
by: Park, Gijun
Published: (2026)
by: Park, Gijun
Published: (2026)
Incentivised Orchestrated Training Architecture (IOTA): A Technical Primer for Release
by: Quinque, Felix, et al.
Published: (2025)
by: Quinque, Felix, et al.
Published: (2025)
GOGH: Correlation-Guided Orchestration of GPUs in Heterogeneous Clusters
by: Raeisi, Ahmad, et al.
Published: (2025)
by: Raeisi, Ahmad, et al.
Published: (2025)
An Ensemble Scheme for Proactive Dominant Data Migration of Pervasive Tasks at the Edge
by: Boulougaris, Georgios, et al.
Published: (2024)
by: Boulougaris, Georgios, et al.
Published: (2024)
Nexus:Proactive Intra-GPU Disaggregation of Prefill and Decode in LLM Serving
by: Shi, Xiaoxiang, et al.
Published: (2025)
by: Shi, Xiaoxiang, et al.
Published: (2025)
Graph Neural Networks and Reinforcement Learning for Proactive Application Image Placement
by: Makris, Antonios, et al.
Published: (2024)
by: Makris, Antonios, et al.
Published: (2024)
Runtime-Orchestrated Second-Order Optimization for Scalable LLM Training
by: Lu, Yishun, et al.
Published: (2026)
by: Lu, Yishun, et al.
Published: (2026)
Intelligent Orchestration of Distributed Large Foundation Model Inference at the Edge
by: Koch, Fernando, et al.
Published: (2025)
by: Koch, Fernando, et al.
Published: (2025)
Decentralized Orchestration Architecture for Fluid Computing: A Secure Distributed AI Use Case
by: Cajaraville-Aboy, Diego, et al.
Published: (2026)
by: Cajaraville-Aboy, Diego, et al.
Published: (2026)
PlexRL: Cluster-Level Orchestration of Serviceized LLM Execution for RLVR
by: Zhang, Yiqi, et al.
Published: (2026)
by: Zhang, Yiqi, et al.
Published: (2026)
Time-Series Learning for Proactive Fault Prediction in Distributed Systems with Deep Neural Structures
by: Wang, Yang, et al.
Published: (2025)
by: Wang, Yang, et al.
Published: (2025)
MoE-SpeQ: Speculative Quantized Decoding with Proactive Expert Prefetching and Offloading for Mixture-of-Experts
by: Wang, Wenfeng, et al.
Published: (2025)
by: Wang, Wenfeng, et al.
Published: (2025)
Orthogonal Calibration for Asynchronous Federated Learning
by: Zhang, Jiayun, et al.
Published: (2025)
by: Zhang, Jiayun, et al.
Published: (2025)
Evaluating Container Orchestration for Neuromorphic Workloads in Virtual Edge Environments
by: Pham, Huyen, et al.
Published: (2026)
by: Pham, Huyen, et al.
Published: (2026)
QAISim: A Toolkit for Modeling and Simulation of AI in Quantum Cloud Computing Environments
by: Singh, Irwindeep, et al.
Published: (2025)
by: Singh, Irwindeep, et al.
Published: (2025)
An Interference-aware Approach for Co-located Container Orchestration with Novel Metric
by: Li, Xiang, et al.
Published: (2024)
by: Li, Xiang, et al.
Published: (2024)
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
by: Peng, Hongyi, et al.
Published: (2024)
by: Peng, Hongyi, et al.
Published: (2024)
EcoServe: Enabling Cost-effective LLM Serving with Proactive Intra- and Inter-Instance Orchestration
by: Du, Jiangsu, et al.
Published: (2025)
by: Du, Jiangsu, et al.
Published: (2025)
A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing
by: Singh, Samaresh Kumar, et al.
Published: (2026)
by: Singh, Samaresh Kumar, et al.
Published: (2026)
Low-Latency Layer-Aware Proactive and Passive Container Migration in Meta Computing
by: Liu, Mengjie, et al.
Published: (2024)
by: Liu, Mengjie, et al.
Published: (2024)
SmartWatts: Self-Calibrating Software-Defined Power Meter for Containers
by: Fieni, Guillaume, et al.
Published: (2020)
by: Fieni, Guillaume, et al.
Published: (2020)
Osmotic Learning: A Self-Supervised Paradigm for Decentralized Contextual Data Representation
by: Colosi, Mario, et al.
Published: (2025)
by: Colosi, Mario, et al.
Published: (2025)
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes
by: Xiao, Youshao, et al.
Published: (2024)
by: Xiao, Youshao, et al.
Published: (2024)
FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
by: Li, Li, et al.
Published: (2021)
by: Li, Li, et al.
Published: (2021)
FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning
by: Li, Daoyuan, et al.
Published: (2025)
by: Li, Daoyuan, et al.
Published: (2025)
Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning
by: Chen, Sijia, et al.
Published: (2024)
by: Chen, Sijia, et al.
Published: (2024)
Unicron: Economizing Self-Healing LLM Training at Scale
by: He, Tao, et al.
Published: (2023)
by: He, Tao, et al.
Published: (2023)
FloatSOM: GPU-Accelerated, Distributed, Topology-Flexible Self-Organizing Maps
by: Xu, Tony, et al.
Published: (2026)
by: Xu, Tony, et al.
Published: (2026)
Sentinel: Dynamic Knowledge Distillation for Personalized Federated Intrusion Detection in Heterogeneous IoT Networks
by: Singh, Gurpreet, et al.
Published: (2025)
by: Singh, Gurpreet, et al.
Published: (2025)
Quasar: Quantized Self-Speculative Acceleration for Rapid Inference via Memory-Efficient Verification
by: Huang, Guang, et al.
Published: (2026)
by: Huang, Guang, et al.
Published: (2026)
Beyond Model Scale Limits: End-Edge-Cloud Federated Learning with Self-Rectified Knowledge Agglomeration
by: Wu, Zhiyuan, et al.
Published: (2025)
by: Wu, Zhiyuan, et al.
Published: (2025)
Efficient AllReduce with Stragglers
by: Devraj, Arjun, et al.
Published: (2025)
by: Devraj, Arjun, et al.
Published: (2025)
TD3-Sched: Learning to Orchestrate Container-based Cloud-Edge Resources via Distributed Reinforcement Learning
by: Song, Shengye, et al.
Published: (2025)
by: Song, Shengye, et al.
Published: (2025)
Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids
by: Banerjee, Roopkatha, et al.
Published: (2025)
by: Banerjee, Roopkatha, et al.
Published: (2025)
ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads
by: Zuo, Jingwei, et al.
Published: (2026)
by: Zuo, Jingwei, et al.
Published: (2026)
Understanding and Improving Communication Performance in Multi-node LLM Inference
by: Singhania, Prajwal, et al.
Published: (2025)
by: Singhania, Prajwal, et al.
Published: (2025)
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler
by: Li, Zilinghan, et al.
Published: (2023)
by: Li, Zilinghan, et al.
Published: (2023)
Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI
by: Kandogan, Eser, et al.
Published: (2025)
by: Kandogan, Eser, et al.
Published: (2025)
Similar Items
-
FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration
by: Hu, Zhengding, et al.
Published: (2026) -
AAPA: An Archetype-Aware Predictive Autoscaler with Uncertainty Quantification for Serverless Workloads on Kubernetes
by: Zhang, Guilin, et al.
Published: (2025) -
Quantifying Autoscaler Vulnerabilities: An Empirical Study of Resource Misallocation Induced by Cloud Infrastructure Faults
by: Park, Gijun
Published: (2026) -
Incentivised Orchestrated Training Architecture (IOTA): A Technical Primer for Release
by: Quinque, Felix, et al.
Published: (2025) -
GOGH: Correlation-Guided Orchestration of GPUs in Heterogeneous Clusters
by: Raeisi, Ahmad, et al.
Published: (2025)