Energy-Efficient Computing Offloading Policy for MEC-assisted Power Sensor Network: A D3QN Approach-Reference-Cited by-同舟云学术

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Energy-Efficient Computing Offloading Policy for MEC-assisted Power Sensor Network: A D3QN Approach

Published:2023-10-20 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Cyber-Physical Social Intelligence (ICCSI)
language:
Short-container-title:

Author:

Guan Ti¹,Yao Yushun²,Yuan Chao³,Liu Fuhao²,Liu Yirong⁴,Gu Rentao²

Affiliation:

1. State Grid Shandong Electric Power Company,Jinan,China

2. Beijing University of Posts and Telecommunications,School of Information and Communication Engineering,Beijing,China

3. State Grid Laiwu Electric Power Supply Company,Jinan,China

4. State Grid Binzhou Electric Power Supply Company,Binzhou,China

Funder

State Grid Corporation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10303765/10303774/10303951.pdf?arnumber=10303951

Reference9 articles.

1. Performance Comparison of Various Wireless Sensor Network Dataset using Deep Learning Classifications

2. Energy-Efficient Data Collection in UAV Enabled Wireless Sensor Network

3. Computation Offloading for Mobile-Edge Computing with Multi-user

4. Edge-Cloud Collaborative Computation Offloading Model Based on Improved Partical Swarm Optimization in MEC

5. Deep reinforcement learning based computation offloading and resource allocation for MEC

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