Machine and deep learning for resource allocation in multi-access edge computing: A survey
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
“DRL+ FL”: An intelligent resource allocation model based on deep reinforcement learning for mobile edge computing
N Shan, X Cui, Z Gao - Computer Communications, 2020 - Elsevier
With the emergence of a large number of computation-intensive and time-sensitive
applications, smart terminal devices with limited resources can only run the model training …
applications, smart terminal devices with limited resources can only run the model training …
Computation offloading in multi-access edge computing networks: A multi-task learning approach
Multi-access edge computing (MEC) has already shown the potential in enabling mobile
devices to bear the computation-intensive applications by offloading some tasks to a nearby …
devices to bear the computation-intensive applications by offloading some tasks to a nearby …
Intelligent offloading in multi-access edge computing: A state-of-the-art review and framework
Multi-access edge computing (MEC), which is deployed in the proximity area of the mobile
user side as a supplement to the traditional remote cloud center, has been regarded as a …
user side as a supplement to the traditional remote cloud center, has been regarded as a …
[HTML][HTML] Resource Allocation in Multi-access Edge Computing for 5G-and-beyond networks
Innovative services with strict requirements are expected in the fifth generation (5G) of
mobile networks and beyond. For example, the Ultra-Reliable Low-Latency Communication …
mobile networks and beyond. For example, the Ultra-Reliable Low-Latency Communication …
When deep reinforcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5G ultradense …
Recently, smart cities, healthcare system, and smart vehicles have raised challenges on the
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
Q-learning algorithm for joint computation offloading and resource allocation in edge cloud
The advent of 5G technology along with the high proliferation of mobile devices entail an
explosion of mobile traffic. Due to their resource-limitation constraint, mobile devices resort …
explosion of mobile traffic. Due to their resource-limitation constraint, mobile devices resort …
Cooperative computation offloading for multi-access edge computing in 6G mobile networks via soft actor critic
Driven by numerous emerging services and applications of mobile devices, multi-access
edge computing (MEC) is regarded as a promising technique for massive Internet of Things …
edge computing (MEC) is regarded as a promising technique for massive Internet of Things …
[HTML][HTML] Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing
The rapid growth of mobile internet services has yielded a variety of computation-intensive
applications such as virtual/augmented reality. Mobile Edge Computing (MEC), which …
applications such as virtual/augmented reality. Mobile Edge Computing (MEC), which …
Task-driven resource assignment in mobile edge computing exploiting evolutionary computation
The IoT network allows IoT devices to communicate with other devices, applications, and
services by exploiting existing network infrastructure. Recently, a promising paradigm, MEC …
services by exploiting existing network infrastructure. Recently, a promising paradigm, MEC …