Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
Joint Long-Term Processed Task and Communication Delay Optimization in UAV-Assisted MEC Systems Using DQN
Mobile Edge Computing (MEC) assisted by Unmanned Aerial Vehicle (UAV) has been widely investigated as a promising system for future Internet-of-Things (IoT) networks. In this context, delay-sensitive tasks of IoT devices…
Edge-computingA Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures
Developing dedicated mixed-signal neuromorphic computing systems optimized for real-time sensory-processing in extreme edge-computing applications requires time-consuming design, fabrication, and deployment of full-custo…
Edge-computingGPUSHFL: Secure Hierarchical Federated Learning Framework for Edge Networks
Federated Learning (FL) is a distributed machine learning paradigm designed for privacy-sensitive applications that run on resource-constrained devices with non-Identically and Independently Distributed (IID) data. Tradi…
Data PoisoningEdge-computingFederated LearningFLeNS: Federated Learning with Enhanced Nesterov-Newton Sketch
Federated learning faces a critical challenge in balancing communication efficiency with rapid convergence, especially for second-order methods. While Newton-type algorithms achieve linear convergence in communication ro…
Dimensionality ReductionEdge-computingFederated LearningSecond-order methodsEnergy-Efficient Multi-UAV-Enabled MEC Systems over Space-Air-Ground Integrated Networks
With the development of artificial intelligence integrated next-generation communication networks, mobile users (MUs) are increasingly demanding the efficient processing of computation-intensive and latency-sensitive tas…
Edge-computingDelay Minimization for Movable Antennas-Enabled Anti-Jamming Communications With Mobile Edge Computing
In future 6G networks, anti-jamming will become a critical challenge, particularly with the development of intelligent jammers that can initiate malicious interference, posing a significant security threat to communicati…
Edge-computingPositionExploring Scaling Laws for Local SGD in Large Language Model Training
This paper investigates scaling laws for local SGD in LLM training, a distributed optimization algorithm that facilitates training on loosely connected devices. Through extensive experiments, we show that local SGD achie…
Distributed OptimizationEdge-computingLanguage ModelingLanguage Modelling+1Enhancing TinyBERT for Financial Sentiment Analysis Using GPT-Augmented FinBERT Distillation
In the rapidly evolving field of financial sentiment analysis, the efficiency and accuracy of predictive models are critical due to their significant impact on financial markets. Transformer based models like BERT and la…
Data AugmentationEdge-computingKnowledge DistillationSentiment AnalysisHyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network
Convolutional neural network (CNN) performs well in Hyperspectral Image (HSI) classification tasks, but its high energy consumption and complex network structure make it difficult to directly apply it to edge computing d…
ClassificationEdge-computingHyperspectral Image Classificationimage-classification+1Machine listening in a neonatal intensive care unit
Oxygenators, alarm devices, and footsteps are some of the most common sound sources in a hospital. Detecting them has scientific value for environmental psychology but comes with challenges of its own: namely, privacy pr…
Cloud ComputingEdge-computingTime SeriesOIDM: An Observability-based Intelligent Distributed Edge Sensing Method for Industrial Cyber-Physical Systems
Industrial cyber-physical systems (ICPS) integrate physical processes with computational and communication technologies in industrial settings. With the support of edge computing technology, it is feasible to schedule la…
Deep Reinforcement LearningEdge-computingSchedulingReal-time Multi-view Omnidirectional Depth Estimation System for Robots and Autonomous Driving on Real Scenes
Omnidirectional Depth Estimation has broad application prospects in fields such as robotic navigation and autonomous driving. In this paper, we propose a robotic prototype system and corresponding algorithm designed to v…
Autonomous DrivingDepth EstimationEdge-computingTera-SpaceCom: GNN-based Deep Reinforcement Learning for Joint Resource Allocation and Task Offloading in TeraHertz Band Space Networks
Terahertz (THz) space communications (Tera-SpaceCom) is envisioned as a promising technology to enable various space science and communication applications. Mainly, the realm of Tera-SpaceCom consists of THz sensing for …
Deep Reinforcement LearningEdge-computingGraph Neural NetworkA Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition
In the human activity recognition research area, prior studies predominantly concentrate on leveraging advanced algorithms on public datasets to enhance recognition performance, little attention has been paid to executin…
Activity RecognitionEdge-computingHuman Activity RecognitionPredictive Coding with Spiking Neural Networks: a Survey
In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding. Specifically, we review the general framework of predictive processing in the context o…
Edge-computingPredictionSurveyInstInfer: In-Storage Attention Offloading for Cost-Effective Long-Context LLM Inference
The widespread of Large Language Models (LLMs) marks a significant milestone in generative AI. Nevertheless, the increasing context length and batch size in offline LLM inference escalate the memory requirement of the ke…
Edge-computingGPUTS-EoH: An Edge Server Task Scheduling Algorithm Based on Evolution of Heuristic
With the widespread adoption of 5G and Internet of Things (IoT) technologies, the low latency provided by edge computing has great importance for real-time processing. However, managing numerous simultaneous service requ…
Edge-computingSchedulingBrain-Inspired Online Adaptation for Remote Sensing with Spiking Neural Network
On-device computing, or edge computing, is becoming increasingly important for remote sensing, particularly in applications like deep network-based perception on on-orbit satellites and unmanned aerial vehicles (UAVs). I…
Domain AdaptationDomain GeneralizationEdge-computingEdge AI: Evaluation of Model Compression Techniques for Convolutional Neural Networks
This work evaluates the compression techniques on ConvNeXt models in image classification tasks using the CIFAR-10 dataset. Structured pruning, unstructured pruning, and dynamic quantization methods are evaluated to redu…
Edge-computingimage-classificationImage ClassificationModel Compression+1Two-Timescale Synchronization and Migration for Digital Twin Networks: A Multi-Agent Deep Reinforcement Learning Approach
Digital twins (DTs) have emerged as a promising enabler for representing the real-time states of physical worlds and realizing self-sustaining systems. In practice, DTs of physical devices, such as mobile users (MUs), ar…
Deep Reinforcement LearningEdge-computing