Enhancing Predictive Maintenance in Mining Mobile Machinery through a TinyML-enabled Hierarchical Inference Network
Fuente:
arXiv
Guardado en:
| Autores principales: | de la Fuente, Raúl, Radrigan, Luciano, Morales, Anibal S |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Agentic TinyML for Intent-aware Handover in 6G Wireless Networks
por: Saleh, Alaa, et al.
Publicado: (2025)
por: Saleh, Alaa, et al.
Publicado: (2025)
Optimizing Split Learning Latency in TinyML-Based IoT Systems
por: Jenhani, Zied, et al.
Publicado: (2025)
por: Jenhani, Zied, et al.
Publicado: (2025)
Reconfigurable Intelligent Surface Assisted VEC Based on Multi-Agent Reinforcement Learning
por: Qi, Kangwei, et al.
Publicado: (2024)
por: Qi, Kangwei, et al.
Publicado: (2024)
A Distributed Event-Triggered Control Strategy for DC Microgrids Based on Publish-Subscribe Model Over Industrial Wireless Sensor Networks
por: Alavi, Seyed Amir, et al.
Publicado: (2019)
por: Alavi, Seyed Amir, et al.
Publicado: (2019)
Cordial Miners: Fast and Efficient Consensus for Every Eventuality
por: Keidar, Idit, et al.
Publicado: (2022)
por: Keidar, Idit, et al.
Publicado: (2022)
Scaling Mobile Agent Systems: From Capability Density to Collective Intelligence
por: He, Bowei
Publicado: (2026)
por: He, Bowei
Publicado: (2026)
Resilient by Design -- Active Inference for Distributed Continuum Intelligence
por: Donta, Praveen Kumar, et al.
Publicado: (2025)
por: Donta, Praveen Kumar, et al.
Publicado: (2025)
Intent-driven Diffusion-based Path for Mobile Data Collector in IoT-enabled Dense WSNs
por: Boda, Uma Mahesh, et al.
Publicado: (2026)
por: Boda, Uma Mahesh, et al.
Publicado: (2026)
Asynchronous MultiAgent Reinforcement Learning for 5G Routing under Side Constraints
por: Racedo, Sebastian, et al.
Publicado: (2026)
por: Racedo, Sebastian, et al.
Publicado: (2026)
Optimizing Age of Information in Vehicular Edge Computing with Federated Graph Neural Network Multi-Agent Reinforcement Learning
por: Wang, Wenhua, et al.
Publicado: (2024)
por: Wang, Wenhua, et al.
Publicado: (2024)
Quality-of-Service Aware LLM Routing for Edge Computing with Multiple Experts
por: Yang, Jin, et al.
Publicado: (2025)
por: Yang, Jin, et al.
Publicado: (2025)
MOD-X: A Modular Open Decentralized eXchange Framework proposal for Heterogeneous Interoperable Artificial Intelligence Agents
por: Ioannides, Georgios, et al.
Publicado: (2025)
por: Ioannides, Georgios, et al.
Publicado: (2025)
UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces
por: Saleh, Alaa, et al.
Publicado: (2025)
por: Saleh, Alaa, et al.
Publicado: (2025)
Over-the-Top Resource Broker System for Split Computing: An Approach to Distribute Cloud Computing Infrastructure
por: Friese, Ingo, et al.
Publicado: (2025)
por: Friese, Ingo, et al.
Publicado: (2025)
MULTI-SCOUT: Multistatic Integrated Sensing and Communications in 5G and Beyond for Moving Target Detection, Positioning, and Tracking
por: Sagduyu, Yalin E., et al.
Publicado: (2025)
por: Sagduyu, Yalin E., et al.
Publicado: (2025)
Hierarchical Learning and Computing over Space-Ground Integrated Networks
por: Zhu, Jingyang, et al.
Publicado: (2024)
por: Zhu, Jingyang, et al.
Publicado: (2024)
Reimagining RDMA Through the Lens of ML
por: Warraich, Ertza, et al.
Publicado: (2025)
por: Warraich, Ertza, et al.
Publicado: (2025)
Multitier Service Migration Framework Based on Mobility Prediction in Mobile Edge Computing
por: Yang, Run, et al.
Publicado: (2024)
por: Yang, Run, et al.
Publicado: (2024)
Grassroots Systems: Concept, Examples, Implementation and Applications
por: Shapiro, Ehud
Publicado: (2023)
por: Shapiro, Ehud
Publicado: (2023)
Scalability limitations of Kademlia DHTs when enabling Data Availability Sampling in Ethereum
por: Cortes-Goicoechea, Mikel, et al.
Publicado: (2024)
por: Cortes-Goicoechea, Mikel, et al.
Publicado: (2024)
OptiNIC: A Resilient and Tail-Optimal RDMA NIC for Distributed ML Workloads
por: Warraich, Ertza, et al.
Publicado: (2025)
por: Warraich, Ertza, et al.
Publicado: (2025)
Palladium: A DPU-enabled Multi-Tenant Serverless Cloud over Zero-copy Multi-node RDMA Fabrics
por: Qi, Shixiong, et al.
Publicado: (2025)
por: Qi, Shixiong, et al.
Publicado: (2025)
AllReduce Scheduling with Hierarchical Deep Reinforcement Learning
por: Wei, Yufan, et al.
Publicado: (2025)
por: Wei, Yufan, et al.
Publicado: (2025)
Strategic Server Deployment under Uncertainty in Mobile Edge Computing
por: Tran, Duc A., et al.
Publicado: (2025)
por: Tran, Duc A., et al.
Publicado: (2025)
Contention-Aware Microservice Deployment in Collaborative Mobile Edge Networks
por: Ge, Xinlei, et al.
Publicado: (2024)
por: Ge, Xinlei, et al.
Publicado: (2024)
Decentralized Network Topology Design for Task Offloading in Mobile Edge Computing
por: Ma, Ke, et al.
Publicado: (2024)
por: Ma, Ke, et al.
Publicado: (2024)
SPARC-LoRa: A Scalable, Power-efficient, Affordable, Reliable, and Cloud Service-enabled LoRa Networking System for Agriculture Applications
por: Wang, Xi, et al.
Publicado: (2024)
por: Wang, Xi, et al.
Publicado: (2024)
Dynamic Hierarchical Birkhoff-von Neumann Decomposition for All-to-All GPU Communication
por: Wu, Yen-Chieh, et al.
Publicado: (2026)
por: Wu, Yen-Chieh, et al.
Publicado: (2026)
Contextual Chain: Single-State Ledger Design for Mobile/IoT Networks with Frequent Partitions
por: Kim, Song-Ju
Publicado: (2026)
por: Kim, Song-Ju
Publicado: (2026)
LIMO: Load-balanced Offloading with MAPE and Particle Swarm Optimization in Mobile Fog Networks
por: Seraj, Yasaman, et al.
Publicado: (2024)
por: Seraj, Yasaman, et al.
Publicado: (2024)
EdgeTimer: Adaptive Multi-Timescale Scheduling in Mobile Edge Computing with Deep Reinforcement Learning
por: Hao, Yijun, et al.
Publicado: (2024)
por: Hao, Yijun, et al.
Publicado: (2024)
SARS: A Resource Selection Algorithm for Autonomous Driving Tasks in Heterogeneous Mobile Edge Computing
por: Zakerian, Reza, et al.
Publicado: (2024)
por: Zakerian, Reza, et al.
Publicado: (2024)
POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning
por: Shirmarz, Alireza, et al.
Publicado: (2025)
por: Shirmarz, Alireza, et al.
Publicado: (2025)
Causal Inference for Quantifying Noisy Neighbor Effects in Multi-Tenant Cloud Environments
por: Schiavo, Philipe S., et al.
Publicado: (2026)
por: Schiavo, Philipe S., et al.
Publicado: (2026)
Temporal-Aware GPU Resource Allocation for Distributed LLM Inference via Reinforcement Learning
por: Du, Chengze, et al.
Publicado: (2025)
por: Du, Chengze, et al.
Publicado: (2025)
PerLLM: Personalized Inference Scheduling with Edge-Cloud Collaboration for Diverse LLM Services
por: Yang, Zheming, et al.
Publicado: (2024)
por: Yang, Zheming, et al.
Publicado: (2024)
Resource Sharing in the Edge: A Distributed Bargaining-Theoretic Approach
por: Zafari, Faheem, et al.
Publicado: (2020)
por: Zafari, Faheem, et al.
Publicado: (2020)
Hierarchical Online-Scheduling for Energy-Efficient Split Inference with Progressive Transmission
por: Tang, Zengzipeng, et al.
Publicado: (2026)
por: Tang, Zengzipeng, et al.
Publicado: (2026)
MOFCO: Mobility- and Migration-Aware Task Offloading in Three-Layer Fog Computing Environments
por: Mahdizadeh, Soheil, et al.
Publicado: (2025)
por: Mahdizadeh, Soheil, et al.
Publicado: (2025)
A Task Decomposition and Planning Framework for Efficient LLM Inference in AI-Enabled WiFi-Offload Networks
por: Han, Mingqi, et al.
Publicado: (2026)
por: Han, Mingqi, et al.
Publicado: (2026)
Ejemplares similares
-
Agentic TinyML for Intent-aware Handover in 6G Wireless Networks
por: Saleh, Alaa, et al.
Publicado: (2025) -
Optimizing Split Learning Latency in TinyML-Based IoT Systems
por: Jenhani, Zied, et al.
Publicado: (2025) -
Reconfigurable Intelligent Surface Assisted VEC Based on Multi-Agent Reinforcement Learning
por: Qi, Kangwei, et al.
Publicado: (2024) -
A Distributed Event-Triggered Control Strategy for DC Microgrids Based on Publish-Subscribe Model Over Industrial Wireless Sensor Networks
por: Alavi, Seyed Amir, et al.
Publicado: (2019) -
Cordial Miners: Fast and Efficient Consensus for Every Eventuality
por: Keidar, Idit, et al.
Publicado: (2022)