Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
Optimizing Federated Learning in LEO Satellite Constellations via Intra-Plane Model Propagation and Sink Satellite Scheduling
The advances in satellite technology developments have recently seen a large number of small satellites being launched into space on Low Earth orbit (LEO) to collect massive data such as Earth observational imagery. The …
Edge-computingFederated LearningSchedulingPost Quantum Secure Blockchain-based Federated Learning for Mobile Edge Computing
Mobile Edge Computing (MEC) has been a promising paradigm for communicating and edge processing of data on the move. We aim to employ Federated Learning (FL) and prominent features of blockchain into MEC architecture suc…
Autonomous VehiclesEdge-computingFederated LearningFrankenSplit: Efficient Neural Feature Compression with Shallow Variational Bottleneck Injection for Mobile Edge Computing
The rise of mobile AI accelerators allows latency-sensitive applications to execute lightweight Deep Neural Networks (DNNs) on the client side. However, critical applications require powerful models that edge devices can…
Data CompressionEdge-computingFeature CompressionImage Classification+3Energy-Efficient Blockchain-enabled User-Centric Mobile Edge Computing
In the traditional mobile edge computing (MEC) system, the availability of MEC services is greatly limited for the edge users of the cell due to serious signal attenuation and inter-cell interference. User-centric MEC (U…
Edge-computingFederatedTrust: A Solution for Trustworthy Federated Learning
The rapid expansion of the Internet of Things (IoT) and Edge Computing has presented challenges for centralized Machine and Deep Learning (ML/DL) methods due to the presence of distributed data silos that hold sensitive …
Edge-computingFairnessFederated LearningPrivacy PreservingVirtualization of Tiny Embedded Systems with a robust real-time capable and extensible Stack Virtual Machine REXAVM supporting Material-integrated Intelligent Systems and Tiny Machine Learning
In the past decades, there has been a significant increase in sensor density and sensor deployment, driven by a significant miniaturization and decrease in size down to the chip level, addressing ubiquitous computing, ed…
Edge-computingViTA: A Vision Transformer Inference Accelerator for Edge Applications
Vision Transformer models, such as ViT, Swin Transformer, and Transformer-in-Transformer, have recently gained significant traction in computer vision tasks due to their ability to capture the global relation between fea…
Edge-computingA Pervasive Framework for Human Detection and Tracking
The advent of the Edge Computing (EC) leads to a huge ecosystem where numerous nodes can interact with data collection devices located close to end users. Human detection and tracking can be realized at edge nodes that p…
Edge-computingHuman DetectionA Comprehensive Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniques
The union of Edge Computing (EC) and Artificial Intelligence (AI) has brought forward the Edge AI concept to provide intelligent solutions close to the end-user environment, for privacy preservation, low latency to real-…
Edge-computingModel CompressionEdgeYOLO: An Edge-Real-Time Object Detector
This paper proposes an efficient, low-complexity and anchor-free object detector based on the state-of-the-art YOLO framework, which can be implemented in real time on edge computing platforms. We develop an enhanced dat…
Data AugmentationEdge-computingObjectA Bandit Approach to Online Pricing for Heterogeneous Edge Resource Allocation
Edge Computing (EC) offers a superior user experience by positioning cloud resources in close proximity to end users. The challenge of allocating edge resources efficiently while maximizing profit for the EC platform rem…
Edge-computingThompson SamplingTo Risk or Not to Risk: Learning with Risk Quantification for IoT Task Offloading in UAVs
A deep reinforcement learning technique is presented for task offloading decision-making algorithms for a multi-access edge computing (MEC) assisted unmanned aerial vehicle (UAV) network in a smart farm Internet of Thing…
Decision MakingDeep Reinforcement LearningEdge-computingFire Detection+3Energy Efficient Computation Offloading in Aerial Edge Networks With Multi-Agent Cooperation
With the high flexibility of supporting resource-intensive and time-sensitive applications, unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is proposed as an innovational paradigm to support the mobile…
Deep Reinforcement LearningEdge-computingSchedulingEnergyShield: Provably-Safe Offloading of Neural Network Controllers for Energy Efficiency
To mitigate the high energy demand of Neural Network (NN) based Autonomous Driving Systems (ADSs), we consider the problem of offloading NN controllers from the ADS to nearby edge-computing infrastructure, but in such a …
Autonomous DrivingEdge-computingEnhance Local Consistency in Federated Learning: A Multi-Step Inertial Momentum Approach
Federated learning (FL), as a collaborative distributed training paradigm with several edge computing devices under the coordination of a centralized server, is plagued by inconsistent local stationary points due to the …
Edge-computingFederated LearningOn Achieving Privacy-Preserving State-of-the-Art Edge Intelligence
Deep Neural Network (DNN) Inference in Edge Computing, often called Edge Intelligence, requires solutions to insure that sensitive data confidentiality and intellectual property are not revealed in the process. Privacy-p…
Edge-computingModel CompressionPositionPrivacy PreservingDifferentially Private Deep Q-Learning for Pattern Privacy Preservation in MEC Offloading
Mobile edge computing (MEC) is a promising paradigm to meet the quality of service (QoS) requirements of latency-sensitive IoT applications. However, attackers may eavesdrop on the offloading decisions to infer the edge …
Edge-computingQ-LearningIntelligent Proactive Fault Tolerance at the Edge through Resource Usage Prediction
The proliferation of demanding applications and edge computing establishes the need for an efficient management of the underlying computing infrastructures, urging the providers to rethink their operational methods. In t…
Edge-computingManagementTopology-aware Federated Learning in Edge Computing: A Comprehensive Survey
The ultra-low latency requirements of 5G/6G applications and privacy constraints call for distributed machine learning systems to be deployed at the edge. With its simple yet effective approach, federated learning (FL) i…
Edge-computingFederated LearningSurveyLesionAid: Vision Transformers-based Skin Lesion Generation and Classification
Skin cancer is one of the most prevalent forms of human cancer. It is recognized mainly visually, beginning with clinical screening and continuing with the dermoscopic examination, histological assessment, and specimen c…
ClassificationData AugmentationEdge-computingExplainable Artificial Intelligence (XAI)+1