Enhancing Sustainable Edge Computing Offloading via Renewable Prediction for Energy Harvesting-Reference-Cited by-同舟云学术

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Enhancing Sustainable Edge Computing Offloading via Renewable Prediction for Energy Harvesting

Published:2024 Issue: Volume:12 Page:74011-74023
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Alhartomi Mohammed¹^ORCID,Salh Adeb²^ORCID,Audah Lukman³^ORCID,Alzahrani Saeed¹^ORCID,Alzahmi Ahmed¹

Affiliation:

1. Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia

2. Faculty of Information and Communication Technology, University Tunku Abdul Rahman, Kampar, Perak, Malaysia

3. Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia

Funder

Deputyship for Research and Innovation, Ministry of Education, Saudi Arabia

Universiti Tunku Abdul Rahman Research Fund (UTARRF) Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10536881.pdf?arnumber=10536881

Reference43 articles.

1. Processor design for portable systems

2. Incentivizing Energy Trading for Interconnected Microgrids

3. Joint Optimization of Data Offloading and Resource Allocation With Renewable Energy Aware for IoT Devices: A Deep Reinforcement Learning Approach

4. A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids

5. Accurate Anomaly Detection With Energy Efficiency in IoT–Edge–Cloud Collaborative Networks

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1. Policy Compression for Intelligent Continuous Control on Low-Power Edge Devices;Sensors;2024-07-27

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