… , mobile-edgecomputing (MEC) is emerging as a promising paradigm by providing computing … To break the curse of high dimensionality in state space, we propose a deep Q-network-…
M Tang, VWS Wong - IEEE Transactions on Mobile Computing, 2020 - ieeexplore.ieee.org
… tasks as well as edge load dynamics, and formulate a task offloading problem to minimize the expected long-term cost. We propose a model-free deepreinforcement learning-based …
R Zhao, X Wang, J Xia, L Fan - Physical Communication, 2020 - Elsevier
… edgecomputing (MEC) networks for intelligent internet of things (IoT), where multiple users have some computational tasks assisted by multiple computational … the deepreinforcement …
X Xiong, K Zheng, L Lei, L Hou - IEEE Journal on Selected …, 2020 - ieeexplore.ieee.org
… edge applications. Thus, we propose a resource allocation policy for the IoT edgecomputing … A deepreinforcement learning approach is applied to solve the problem. We also propose …
H Zhou, K Jiang, X Liu, X Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
… enabled mobile-edgecomputing: A deepreinforcement learning … for mobile edgecomputing by deepreinforcement learning … mobile edgecomputing via deepreinforcement learning for …
Y Zhan, S Guo, P Li, J Zhang - IEEE Transactions on Computers, 2020 - ieeexplore.ieee.org
… computing capability at the edge of pervasive radio access networks close to users. A critical research challenge of edgecomputing … tasks can be offloaded to edge servers with limited …
M Li, J Gao, L Zhao, X Shen - IEEE Transactions on Cognitive …, 2020 - ieeexplore.ieee.org
… Abstract—Mobile edgecomputing (MEC) is a promising technology to support mission-… In this paper, a collaborative edgecomputing framework is developed to reduce the computing …
Y Liu, H Yu, S Xie, Y Zhang - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
… edgecomputing network architecture in which the vehicles can act as the mobile edge … long-term utility of the vehicle edgecomputing network. Considering the stochastic vehicle …
… By employing a deepreinforcement learning method, namely deep Q-learning, we design … at the edgecomputing node to develop a real-time adaptive policy for computational resource …