Copertina

Towards Formal Verification of Federated Learning Orchestration Protocols on Satellites

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Popovic, Miroslav, Popovic, Marko, Djukic, Miodrag, Basicevic, Ilija
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MicroPython Testbed for Federated Learning Algorithms
di: Popovic, Miroslav, et al.
Pubblicazione: (2024)

Developing Elementary Federated Learning Algorithms Leveraging the ChatGPT
di: Popovic, Miroslav, et al.
Pubblicazione: (2023)

Formal Verification of a Generic Algorithm for TDM Communication Over Inter Satellite Links
di: Popovic, Miroslav, et al.
Pubblicazione: (2025)

Generic Algorithm for Universal TDM Communication Over Inter Satellite Links
di: Popovic, Miroslav, et al.
Pubblicazione: (2025)

Translating Federated Learning Algorithms in Python into CSP Processes Using ChatGPT
di: Popovic, Miroslav, et al.
Pubblicazione: (2025)

Fast Transaction Scheduling in Blockchain Sharding
di: Adhikari, Ramesh, et al.
Pubblicazione: (2024)

On the Efficiency of Dynamic Transaction Scheduling in Blockchain Sharding
di: Adhikari, Ramesh, et al.
Pubblicazione: (2025)

Federated Isolation Forest for Efficient Anomaly Detection on Edge IoT Systems
di: Vasiljevic, Pavle, et al.
Pubblicazione: (2025)

Formal Modeling and Verification of the Algorand Consensus Protocol in CADP
di: Esposito, Andrea, et al.
Pubblicazione: (2025)

Inference Load-Aware Orchestration for Hierarchical Federated Learning
di: Lackinger, Anna, et al.
Pubblicazione: (2024)

sat-QFL: Secure Quantum Federated Learning for Low Orbit Satellites
di: Gurung, Dev, et al.
Pubblicazione: (2025)

Orchestrating Federated Learning in Space-Air-Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover
di: Han, Dong-Jun, et al.
Pubblicazione: (2024)

FedHC: A Hierarchical Clustered Federated Learning Framework for Satellite Networks
di: Liu, Zhuocheng, et al.
Pubblicazione: (2025)

FedCod: An Efficient Communication Protocol for Cross-Silo Federated Learning with Coding
di: Yan, Peishen, et al.
Pubblicazione: (2024)

ClusterLess: Deadline-Aware Serverless Workflow Orchestration on Federated Edge Clusters
di: Farahani, Reza, et al.
Pubblicazione: (2026)

Towards Carbon-Aware Container Orchestration: Predicting Workload Energy Consumption with Federated Learning
di: Saad, Zainab, et al.
Pubblicazione: (2025)

DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations
di: Yang, Minghao, et al.
Pubblicazione: (2024)

ALANINE: A Novel Decentralized Personalized Federated Learning For Heterogeneous LEO Satellite Constellation
di: Zhao, Liang, et al.
Pubblicazione: (2024)

Towards System-Oriented Formal Verification of Local-First Access Control
di: Jacob, Florian, et al.
Pubblicazione: (2026)

CroSatFL: Energy-Efficient Federated Learning with Cross-Aggregation for Satellite Edge Computing
di: Yang, Nan, et al.
Pubblicazione: (2026)

Reusable Formal Verification of DAG-based Consensus Protocols
di: Bertrand, Nathalie, et al.
Pubblicazione: (2024)

Towards Adaptive Asynchronous Federated Learning for Human Activity Recognition
di: Gajanin, Rastko, et al.
Pubblicazione: (2024)

AgentX: Towards Orchestrating Robust Agentic Workflow Patterns with FaaS-hosted MCP Services
di: Tokal, Shiva Sai Krishna Anand, et al.
Pubblicazione: (2025)

Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning
di: Elmahallawy, Mohamed, et al.
Pubblicazione: (2024)

Towards Efficient Verification of Parallel Applications with Mc SimGrid
di: Laurent, Matthieu, et al.
Pubblicazione: (2025)

Scheduling for On-Board Federated Learning with Satellite Clusters
di: Razmi, Nasrin, et al.
Pubblicazione: (2024)

Towards Communication-Efficient Decentralized Federated Graph Learning over Non-IID Data
di: Wang, Shilong, et al.
Pubblicazione: (2025)

TD3-Sched: Learning to Orchestrate Container-based Cloud-Edge Resources via Distributed Reinforcement Learning
di: Song, Shengye, et al.
Pubblicazione: (2025)

Orchestrating the Execution of Serverless Functions in Hybrid Clouds
di: Peri, Aristotelis, et al.
Pubblicazione: (2024)

Synergizing Monetization, Orchestration, and Semantics in Computing Continuum
di: Dehury, Chinmaya Kumar, et al.
Pubblicazione: (2025)

Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning
di: Saba, Issa, et al.
Pubblicazione: (2024)

Orchestrating Mixed-Criticality Cloud Workloads in Reconfigurable Manufacturing Systems
di: Barletta, Marco, et al.
Pubblicazione: (2024)

iDDS: Intelligent Distributed Dispatch and Scheduling for Workflow Orchestration
di: Guan, Wen, et al.
Pubblicazione: (2025)

Evaluating Container Orchestration for Neuromorphic Workloads in Virtual Edge Environments
di: Pham, Huyen, et al.
Pubblicazione: (2026)

HARP: Orchestrating Automated Parallel Training on Heterogeneous GPU Clusters
di: Liang, Antian, et al.
Pubblicazione: (2025)

Joint$λ$: Orchestrating Serverless Workflows on Jointcloud FaaS Systems
di: Li, Rui, et al.
Pubblicazione: (2025)

Herring: Parallel Batch-Order-Fairness on DAG-based Blockchain Consensus
di: Putnik, Marko, et al.
Pubblicazione: (2026)

An Interference-aware Approach for Co-located Container Orchestration with Novel Metric
di: Li, Xiang, et al.
Pubblicazione: (2024)

OServe: Accelerating LLM Serving via Spatial-Temporal Workload Orchestration
di: Jiang, Youhe, et al.
Pubblicazione: (2026)

Environmentally-Conscious Cloud Orchestration Considering Geo-Distributed Data Centers
di: Attenni, Giulio, et al.
Pubblicazione: (2025)