Reinforcement learning methods for computation offloading: a systematic review
Z Zabihi, AM Eftekhari Moghadam… - ACM Computing …, 2023 - dl.acm.org
Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …
applications due to the long distance between end-devices and remote datacenters. In …
The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
MAP based modeling method and performance study of a task offloading scheme with time-correlated traffic and VM repair in MEC systems
Y Wang, X Han, S Jin - Wireless Networks, 2023 - Springer
Abstract Mobile Edge Computing (MEC) has evolved into a key technology that can
leverage resources of computing, storage and network deployed at the proximity of the …
leverage resources of computing, storage and network deployed at the proximity of the …
A QoS-aware technique for computation offloading in IoT-edge platforms using a convolutional neural network and Markov decision process
Offloading is one of the critical enablers of the Internet of Things (IoT) as it helps overcome
the resource limitations of individual objects. Offering enough computational power for IoT …
the resource limitations of individual objects. Offering enough computational power for IoT …
Performance optimization of serverless edge computing function offloading based on deep reinforcement learning
X Yao, N Chen, X Yuan, P Ou - Future Generation Computer Systems, 2023 - Elsevier
It is difficult for resource-constrained edge servers to simultaneously meet the performance
requirements of all the latency-sensitive Internet of Things (IoT) applications in edge …
requirements of all the latency-sensitive Internet of Things (IoT) applications in edge …
Resource allocation in DT-assisted Internet of Vehicles via edge intelligent cooperation
Applications in the Internet of Vehicles (IoV) are usually accompanied by ultralow network
response latency requirement. A promising approach to meet this demand is combining the …
response latency requirement. A promising approach to meet this demand is combining the …
Drl-driven joint task offloading and resource allocation for energy-efficient content delivery in cloud-edge cooperation networks
With the proliferation of mobile devices (eg, vehicles and smartphones), rich media content
services from massive users lead to high network resource consumption and energy usage …
services from massive users lead to high network resource consumption and energy usage …
Federated deep reinforcement learning-based task offloading and resource allocation for smart cities in a mobile edge network
X Chen, G Liu - Sensors, 2022 - mdpi.com
Mobile edge computing (MEC) has become an indispensable part of the era of the intelligent
manufacturing industry 4.0. In the smart city, computation-intensive tasks can be offloaded to …
manufacturing industry 4.0. In the smart city, computation-intensive tasks can be offloaded to …
DRL-based secure video offloading in MEC-enabled IoT networks
Wireless offloading in mobile-edge-computing (MEC)-enabled Internet of Things (IoT)
networks inevitably suffers the risk of eavesdropping. Physical-layer security (PLS) …
networks inevitably suffers the risk of eavesdropping. Physical-layer security (PLS) …
Large-scale computation offloading using a multi-agent reinforcement learning in heterogeneous multi-access edge computing
Z Gao, L Yang, Y Dai - IEEE Transactions on Mobile Computing, 2022 - ieeexplore.ieee.org
Recently, existing computation offloading methods have provided extremely low service
latency for mobile users (MUs) in multi-access edge computing (MEC). However, this …
latency for mobile users (MUs) in multi-access edge computing (MEC). However, this …