[HTML][HTML] Network-assisted processing of advanced IoT applications: challenges and proof-of-concept application
Recent advances in the area of the Internet of Things shows that devices are usually
resource-constrained. To enable advanced applications on these devices, it is necessary to …
resource-constrained. To enable advanced applications on these devices, it is necessary to …
AI-based sustainable and intelligent offloading framework for iIoT in collaborative cloud-fog environments
The cloud paradigm is one of the most trending areas in today's era due to its rich profusion
of services. However, it fails to serve the latency-sensitive Industrial Internet of Things (IIoT) …
of services. However, it fails to serve the latency-sensitive Industrial Internet of Things (IIoT) …
A relay-assisted parallel offloading strategy for multi-source tasks in internet of vehicles
D Cao, YB Zhang, YF Yang, BF Ji, PK Sharma… - Sustainable Energy …, 2024 - Elsevier
Abstract Internet of Vehicles (IoV) is paving the road for the new generation of Intelligent
Transportation Systems (ITS), and Mobile Edge Computing (MEC) is enabling IoV to …
Transportation Systems (ITS), and Mobile Edge Computing (MEC) is enabling IoV to …
A Reputation-Enhanced Shard-Based Byzantine Fault-Tolerant Scheme for Secure Data Sharing in Zero Trust Human Digital Twin Systems
Secure data sharing is imperative in human digital twin (HDT) systems due to the continuous
communication requirements among physical and virtual twins, making data security and …
communication requirements among physical and virtual twins, making data security and …
Deep reinforcement learning-based task assignment for cooperative mobile edge computing
Mobile edge computing (MEC) integrates computing resources in wireless access networks
to process computational tasks in close proximity to mobile users with low latency. This …
to process computational tasks in close proximity to mobile users with low latency. This …
Efficient End-Edge-Cloud Task Offloading in 6G Networks Based on Multi-Agent Deep Reinforcement Learning
H She, L Yan, Y Guo - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
With the progressive evolution of the sixth-generation (6G) network, an array of diverse
application tasks is experiencing a steady surge, consequently intensifying the …
application tasks is experiencing a steady surge, consequently intensifying the …
[HTML][HTML] Service-Aware Hierarchical Fog–Cloud Resource Mappingfor e-Health with Enhanced-Kernel SVM
Fog–cloud-based hierarchical task-scheduling methods are embracing significant
challenges to support e-Health applications due to the large number of users, high task …
challenges to support e-Health applications due to the large number of users, high task …
Adaptive Training and Aggregation for Federated Learning in Multi-tier Computing Networks
Multi-tier computing (MC) utilizes computing resources from the cloud, fog, edge, and end
layers to promote intelligent Internet of Things (IoT) applications. Federated learning (FL) in …
layers to promote intelligent Internet of Things (IoT) applications. Federated learning (FL) in …
Lyapunov-Optimized and Energy-Constrained Stable Online Computation Offloading in Wireless Microtremor Sensor Networks
R Tian, H Xing, Y Cao, H Zhang - IEEE Transactions on Signal …, 2024 - ieeexplore.ieee.org
The microtremor survey method (MSM) holds great potential for obtaining subsurface shear
wave velocity structures in exploration geophysics. However, the lack of an instant imaging …
wave velocity structures in exploration geophysics. However, the lack of an instant imaging …
A Survey of Computation Offloading with Task Type
Computation task offloading is one of the enabling technologies for computation-intensive
applications and edge intelligence, which experiences the explosive growth of massive data …
applications and edge intelligence, which experiences the explosive growth of massive data …