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Buraq: A Fast Pod Scheduling Framework for Multi-Cluster Kubernetes with Hard Privacy and Residency Gates

https://doi.org/10.2139/ssrn.7596989
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KTWIN: A serverless Kubernetes-based Digital Twin platform
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kubeFlower: A privacy-preserving framework for Kubernetes-based federated learning in cloud–edge environments
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Managing software build infrastructure at ALICE using Hashicorp Nomad
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The influence of European data privacy standards outside Europe: implications for globalization of Convention 108
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Proactive Stateful Fault-Tolerant System for Kubernetes Containerized Services
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K-TAHP: A Kubernetes Load Balancing Strategy Base on TOPSIS+AHP
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Internet of Things Services Orchestration Framework Based on Kubernetes and Edge Computing
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Toward Highly Scalable Load Balancing in Kubernetes Clusters
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Large-Scale Machine Learning Cluster Scheduling via Multi-Agent Graph Reinforcement Learning
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Delay-Resistant Geo-Distributed Analytics
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Security-Aware and Time-Guaranteed Service Placement in Edge Clouds
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Kano: Efficient Cloud Native Network Policy Verification
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Diktyo: Network-Aware Scheduling in Container-Based Clouds
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Elastic Cross-Layer Orchestration of Network Policies in the Kubernetes Stack
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Vulnerability-Aware Secure Service Deployment in Cloud-Edge Continuum
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Cost-Effective Cloud-Edge Elasticity for Microservice Applications
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A Multi-Objective Framework for Power-Aware Scheduling in Kubernetes
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Sakkara : Intelligent Topology-Aware Scheduling for Kubernetes in the Age of AI
inferredcites →https://doi.org/10.1109/tnsm.2026.3713212openalex-snapshot
Resource Allocation and Container Scaling for Microservices in Multi-Cluster Edge Computing System
inferredcites →https://doi.org/10.1145/2517349.2522716openalex-snapshot
Sparrow
inferredcites →https://doi.org/10.1145/2806777.2806779openalex-snapshot
Tarcil
inferredcites →https://doi.org/10.1145/2890784openalex-snapshot
Borg, Omega, and Kubernetes
inferredcites →https://doi.org/10.1145/3544788openalex-snapshot
Custom Scheduling in Kubernetes: A Survey on Common Problems and Solution Approaches
inferredcites →https://doi.org/10.3390/electronics13132651openalex-snapshot
Evolving High-Performance Computing Data Centers with Kubernetes, Performance Analysis, and Dynamic Workload Placement Based on Machine Learning Scheduling
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On the Optimization of Kubernetes toward the Enhancement of Cloud Computing
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