Online computation offloading via deep convolutional feature map attention reinforcement learning and adaptive rewarding policy

P Anusha, VMA Bai - Wireless Networks, 2023 - Springer
Stability in queue characteristics with average power and maximized data processing is a
prominent research issue in any networks. These should be ensured even in Mobile Edge …

Enhancing Computation Offloading In Wireless-Powered Mobile-Edge Computing Networks With Deep Reinforcement Learning For Online Optimization

RP Kumar, C Spandana, IV Srisurya… - … on Advances in …, 2024 - ieeexplore.ieee.org
Edge computing at the mobile frontier, enhanced by the integration of wireless energy,
represents a cutting-edge strategy to boost processing performance in networks with limited …

Three‐Tier Computing Platform Optimization: A Deep Reinforcement Learning Approach

CS Chidume, SI Okopi, T Sesay… - Mobile Information …, 2022 - Wiley Online Library
The increasing number of computing platforms is critical with the increasing trend of delay‐
sensitive complex applications with enormous power consumption. These computing …

Lyapunov-guided deep reinforcement learning for stable online computation offloading in mobile-edge computing networks

S Bi, L Huang, H Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Opportunistic computation offloading is an effective method to improve the computation
performance of mobile-edge computing (MEC) networks under dynamic edge environment …

ADRLO: Adaptive deep reinforcement learning-based offloading for edge computing

Z Li, Y Wang, W Zhang, S Li, X Sun - Physical Communication, 2023 - Elsevier
Computation offloading, as an efficient and promising computing paradigm for mobile edge
computing (MEC), provides optimal computation allocation between MEC servers and …

A Deep Learning‐Based Algorithm for Energy and Performance Optimization of Computational Offloading in Mobile Edge Computing

I Khan, S Raza, W Rehman, R Khan… - Wireless …, 2023 - Wiley Online Library
Mobile edge computing (MEC) has produced incredible outcomes in the context of
computationally intensive mobile applications by offloading computation to a neighboring …

Learning based latency minimization techniques in mobile edge computing (MEC) systems: A Comprehensive Survey

K Kumaran, E Sasikala - 2021 International conference on …, 2021 - ieeexplore.ieee.org
In current world, processing the data by the users, researchers, organizations, etc. through
online source (ie. cloud) is increasing tremendously, where it offers various services like …

Computation offloading in multi-access edge computing using a deep sequential model based on reinforcement learning

J Wang, J Hu, G Min, W Zhan, Q Ni… - IEEE Communications …, 2019 - ieeexplore.ieee.org
MEC is an emerging paradigm that utilizes computing resources at the network edge to
deploy heterogeneous applications and services. In the MEC system, mobile users and …

Online task offloading in udn: A deep reinforcement learning approach with incomplete information

Z Lin, B Gu, X Zhang, D Yi, Y Han - 2022 IEEE Wireless …, 2022 - ieeexplore.ieee.org
Multi-access edge computing (MEC) and ultra-dense networking (UDN) are recognized as
two promising paradigms for future mobile networks that can be utilized to improve the …

Intelligent Online Computation Offloading for Wireless Powered Mobile Edge Computing

Y Wang, Z Qian, L He, R Yin… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
In the Internet of Things (IoT) ecosystem, optimizing processing capabilities of devices
through Wireless Powered Mobile Edge Computing (WP-MEC) is crucial. This research …