Deep reinforcement learning online offloading for SWIPT multiple access edge computing network

Deep reinforcement learning online offloading for SWIPT multiple access edge computing network

More computation-intensive and low latency applications are emerging recently, and they are constrained by the computing power and battery life of internet of things (IoT). Simultaneous wireless information and power transfer (SWIPT) with mobile-edge computing (MEC) can improve the data processing c...

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Bibliographic Details
Main Authors: Teckchai, Tiong, Ismail Saad, Tze, Kenneth Kin Teo, Herwansyah Lago
Format: Proceedings
Language:English
English
Published: Institute of Electrical and Electronics Engineers 2021
Subjects:
QA76.75-76.765 Computer software
Online Access:https://eprints.ums.edu.my/id/eprint/32718/1/Deep%20reinforcement%20learning%20online%20offloading%20for%20SWIPT%20multiple%20access%20edge%20computing%20network.ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/32718/2/Deep%20Reinforcement%20Learning%20Online%20Offloading%20for%20SWIPT%20Multiple%20Access%20Edge%20Computing%20Network.pdf
https://eprints.ums.edu.my/id/eprint/32718/
https://ieeexplore.ieee.org/document/9612551
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Institution: Universiti Malaysia Sabah
Language: English
English

Internet

https://eprints.ums.edu.my/id/eprint/32718/1/Deep%20reinforcement%20learning%20online%20offloading%20for%20SWIPT%20multiple%20access%20edge%20computing%20network.ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/32718/2/Deep%20Reinforcement%20Learning%20Online%20Offloading%20for%20SWIPT%20Multiple%20Access%20Edge%20Computing%20Network.pdf
https://eprints.ums.edu.my/id/eprint/32718/
https://ieeexplore.ieee.org/document/9612551

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