edge computing

AoI Minimization in Heterogeneous MEC Networks: A Federated Learning-Assisted Hybrid DRL and Convex Approach

This paper investigates a dynamic heterogeneous mobile edge computing network (HMECN), where mobile devices (MDs) could offload their full tasks to a small base station (SBS) directly or the macro base station (MBS) in direct or relay mode. As age of information (AoI) is a comprehensive and accurate metric to capture t...

Chance constraint-based dependent task offloading for multi-access edge computing under uncertainty

Attribute-Based Access Control in Cloud–Edge Industrial IoT Networks via Deep Reinforcement Learning

The fourth industrial revolution drives AI-powered smart manufacturing through cloud-edge computing, enabling intelligent production processes and data-driven automation. To handle security concerns arising from massive IoT deployments, attribute-based access control (ABAC) has become essential for smart factories. It...

Low-Energy Resource Optimization and Task Assignment for Satellite Edge Computing Networks

Satellite edge computing (SEC) has emerged as a promising paradigm to enhance in-orbit data processing capabilities and reduce transmission latency. However, satellite image processing tasks in SEC environments face critical challenges in efficient data handling, resource coordination, and transmission scheduling. The...

Large AI Models Empowered Edge Intelligence for Next-Gen Consumer Electronics

This article addresses challenges in the Internet of Consumer Electronics (ICE), such as random task arrivals, limited resources, and system stability, by proposing a collaborative computing framework that integrates edge intelligence with Lyapunov-based deep reinforcement learning (DRL). The framework adopts a three-t...

Latency-Failure-Aware Multi-Agent Fuzzy Reinforcement Learning for Reliable Service Function Chain Backup

Edge computing-enabled lightweight cross-modality attention fusion for IoT-based physical education systems

DRUDM-CFG: A Fairness-Aware Multi-Agent DRL Algorithm for AMEC-Assisted Task Offloading in Post-Disaster Scenarios

High-altitude airships (HAS) and uncrewed aerial vehicles (UAVs) equipped with Multiaccess Edge Computing (MEC) servers have emerged as promising aerial MEC nodes for providing task offloading (TO) services to intelligent mobile devices (IMDs) in post-disaster scenarios. HAS offers robust computing and energy resources...

Service Satisfaction Based User Selection and Resource Allocation for NOMA-Based Multi-Cell MEC Networks

Mobile Edge Computing (MEC) is promising to enable low delay services with which users can offload computing intensive and delay sensitive tasks to the edge. Considering a multi-cell MEC (MC-MEC) network without sufficient resources to serve all users, user selection and non-orthogonal multiple access (NOMA) should be...

DSCAttenEMG: A Lightweight sEMG-Based Hand Gesture Recognition Model via Depthwise Separable Convolution and Multi-Head Attention

The implementation of surface electromyography (sEMG)-based hand gesture recognition on mobile and wearable systems is frequently restricted by the finite computing, memory, and battery capabilities of edge devices. Even though a low-density sEMG setup is a feasible hardware implementation, achieving robust recognition...

TSFlow: Time-Aware Secure Flow Control for Fine-Grained Data Sharing in Mobile Edge-Cloud

The rise of edge-cloud computing has accelerated data sharing among mobile users. To resist malicious senders within organizations from leaking sensitive data, access control encryption (ACE) schemes have been employed to secure data flows, in which each sender obtains an encryption key according to the access control...

GraphKANLoc: Physics-Informed Heterogeneous Graph Attention Networks With KAN Regression for Indoor Localization