A survey on deep learning based knowledge tracing
Abstract “Knowledge tracing (KT)” is an emerging and popular research topic in the field of
online education that seeks to assess students' mastery of a concept based on their …
online education that seeks to assess students' mastery of a concept based on their …
Local scheduling in kubeedge-based edge computing environment
SH Kim, T Kim - Sensors, 2023 - mdpi.com
KubeEdge is an open-source platform that orchestrates containerized Internet of Things
(IoT) application services in IoT edge computing environments. Based on Kubernetes, it …
(IoT) application services in IoT edge computing environments. Based on Kubernetes, it …
Toward AI-enabled nextG networks with edge intelligence-assisted microservice orchestration
Network agility, automation, and intelligence are at the forefront of the next-generation
networks (NGNs) vision, which aims to provide zero-touch service management and self …
networks (NGNs) vision, which aims to provide zero-touch service management and self …
Node-based horizontal pod autoscaler in kubeedge-based edge computing infrastructure
KubeEdge (KE) is a container orchestration platform for deploying and managing
containerized IoT applications in an edge computing environment based on Kubernetes. It is …
containerized IoT applications in an edge computing environment based on Kubernetes. It is …
Overview of blockchain-based terminal-edge-cloud collaborative computing paradigm
L Li, J Li, R Liu, Z Li - Computers and Electrical Engineering, 2024 - Elsevier
With the rapid development of the Internet of Things (IoT), terminal-edge-cloud collaborative
computing (TECC), a hierarchical distributed computing model, has become an effective …
computing (TECC), a hierarchical distributed computing model, has become an effective …
Energy-Efficient Computing Acceleration of Unmanned Aerial Vehicles Based on a CPU/FPGA/NPU Heterogeneous System
X Liu, W Xu, Q Wang, M Zhang - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The time and energy optimization of computationally intensive tasks involving unmanned air
vehicles (UAVs) is highly important for increasing the reaction speed of UAVs and for …
vehicles (UAVs) is highly important for increasing the reaction speed of UAVs and for …
ECCVideo: A scalable edge cloud collaborative video analysis system
Q Han, X Ren, P Zhao, Y Wang, L Wang… - IEEE Intelligent …, 2022 - ieeexplore.ieee.org
Video analysis drives a wide range of applications in the fields of public safety, autonomous
vehicles, etc., with the great potential to impact society. Traditional cloud-based approaches …
vehicles, etc., with the great potential to impact society. Traditional cloud-based approaches …
ComEdge: Cloud-Native Platform for Integrated Computing and Communication in Satellite–Terrestrial Network
H Shi, X Zhang, P Wu, J Chen, Y Zhang - Electronics, 2023 - mdpi.com
Leveraging technological advancements such as containers, microservices, and service
mesh, cloud-native edge computing (CNEC) has become extensively discussed and applied …
mesh, cloud-native edge computing (CNEC) has become extensively discussed and applied …
Deep Convolutional Linear Precoder Neural Network for Rate Splitting Strategy of Aerial Computing Networks
Aerial computing networks are facing the challenge of massive node access, where user
devices generally have stringent latency and robustness requirements. Rate Splitting …
devices generally have stringent latency and robustness requirements. Rate Splitting …
Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities
With the increasing demand for seamless connectivity and intelligent communication, the
integration of artificial intelligence (AI) and communication for sixth-generation (6G) network …
integration of artificial intelligence (AI) and communication for sixth-generation (6G) network …