Cover Image

When IoT Meet LLMs: Applications and Challenges

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kok, Ibrahim, Demirci, Orhan, Ozdemir, Suat
Format:	Preprint
Published:	2024
Subjects:	Distributed, Parallel, and Cluster Computing Artificial Intelligence Networking and Internet Architecture
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimizing Split Learning Latency in TinyML-Based IoT Systems
by: Jenhani, Zied, et al.
Published: (2025)

When Digital Twin Meets 6G: Concepts, Obstacles, and Research Prospects
by: Liu, Wenshuai, et al.
Published: (2024)

Efficient Fog Node Placement using Nature-Inspired Metaheuristic for IoT Applications
by: Naouri, Abdenacer, et al.
Published: (2023)

A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications
by: Manchanda, Ashish, et al.
Published: (2024)

EdgeLinker: Practical Blockchain-based Framework for Healthcare Fog Applications to Enhance Security in Edge-IoT Data Communications
by: Zarkesh, Mahdi Akbari, et al.
Published: (2024)

Dynamic and Distributed Routing in IoT Networks based on Multi-Objective Q-Learning
by: Vaishnav, Shubham, et al.
Published: (2025)

Channel Access Methods for RF-Powered IoT Networks: A Survey
by: Yu, Hang, et al.
Published: (2024)

SLA Conceptual Model for IoT Applications
by: Alqahtani, Awatif, et al.
Published: (2024)

Contextual Chain: Single-State Ledger Design for Mobile/IoT Networks with Frequent Partitions
by: Kim, Song-Ju
Published: (2026)

Intent-driven Diffusion-based Path for Mobile Data Collector in IoT-enabled Dense WSNs
by: Boda, Uma Mahesh, et al.
Published: (2026)

Digital Twinning of a Pressurized Water Reactor Startup Operation and Partial Computational Offloading in In-network Computing-Assisted Multiaccess Edge Computing
by: Aliyu, Ibrahim, et al.
Published: (2024)

Towards Edge General Intelligence via Large Language Models: Opportunities and Challenges
by: Chen, Handi, et al.
Published: (2024)

Jupiter: Fast and Resource-Efficient Collaborative Inference of Generative LLMs on Edge Devices
by: Ye, Shengyuan, et al.
Published: (2025)

Deduplicator: When Computation Reuse Meets Load Balancing at the Network Edge
by: Azad, Md Washik Al, et al.
Published: (2024)

Teola: Towards End-to-End Optimization of LLM-based Applications
by: Tan, Xin, et al.
Published: (2024)

Diffusion Models on the Edge: Challenges, Optimizations, and Applications
by: Zheng, Dongqi
Published: (2025)

Privacy-Preserving IoT in Connected Aircraft Cabin
by: Vyas, Nilesh, et al.
Published: (2025)

NebulaFL: Effective Asynchronous Federated Learning for JointCloud Computing
by: Gao, Fei, et al.
Published: (2024)

Context-Aware Orchestration of Energy-Efficient Gossip Learning Schemes
by: Dinani, Mina Aghaei, et al.
Published: (2024)

Design and Optimization of Hierarchical Gradient Coding for Distributed Learning at Edge Devices
by: Tang, Weiheng, et al.
Published: (2024)

Adaptive Parameter-Efficient Federated Fine-Tuning on Heterogeneous Devices
by: Liu, Jun, et al.
Published: (2024)

An Open API Architecture to Discover the Trustworthy Explanation of Cloud AI Services
by: Wang, Zerui, et al.
Published: (2024)

Rina: Enhancing Ring-AllReduce with In-network Aggregation in Distributed Model Training
by: Chen, Zixuan, et al.
Published: (2024)

Collective Communication Profiling of Modern-day Machine Learning Workloads
by: Gupta, Jit, et al.
Published: (2025)

HALO: Semantic-Aware Distributed LLM Inference in Lossy Edge Network
by: Zheng, Peirong, et al.
Published: (2026)

Optimizing Resource Allocation for Geographically-Distributed Inference by Large Language Models
by: Sun, Tingyang, et al.
Published: (2025)

Towards Net-Zero Carbon Emissions in Network AI for 6G and Beyond
by: Zhang, Peng, et al.
Published: (2023)

Trust-Aware Routing for Distributed Generative AI Inference at the Edge
by: Nguyen, Chanh, et al.
Published: (2026)

Agentic Performance at the Edge: Insights from Benchmarking
by: Wang, Shiqiang, et al.
Published: (2026)

KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving
by: Liu, Zedong, et al.
Published: (2026)

AI Greenferencing: Routing AI Inferencing to Green Modular Data Centers with Heron
by: Reddy, Tella Rajashekhar, et al.
Published: (2025)

Cluster Topology-Driven Placement of Experts Reduces Network Traffic in MoE Inference
by: Sivtsov, Danil, et al.
Published: (2025)

High-speed Networking for Giga-Scale AI Factories
by: Khashab, Sajy, et al.
Published: (2026)

ScaleAcross Explorer: Exploring Communication Optimization for Scale-Across AI Model Training
by: Li, Minghao, et al.
Published: (2026)

Move the Query, Not the Cache: Characterizing Cross-Instance Latent Attention Redistribution Across GPU Fabrics
by: Ma, Bole, et al.
Published: (2026)

The Implications of Decentralization in Blockchained Federated Learning: Evaluating the Impact of Model Staleness and Inconsistencies
by: Wilhelmi, Francesc, et al.
Published: (2023)

Enabling Reconfiguration-Communication Overlap for Collective Communication in Optical Networks
by: Wu, Changbo, et al.
Published: (2025)

Smaller, Smarter, Closer: The Edge of Collaborative Generative AI
by: Morabito, Roberto, et al.
Published: (2025)

eACGM: Non-instrumented Performance Tracing and Anomaly Detection towards Machine Learning Systems
by: Xu, Ruilin, et al.
Published: (2025)

SpaceMoE: Realizing Distributed Mixture-of-Experts Inference over Space Networks
by: Wang, Zhanwei, et al.
Published: (2026)