Staff View: Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based

Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based

The emergence of the sixth generation (6G) wireless networks brings new challenges and opportunities for efficient computing offloading and resource allocation. This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G netw...

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Main Authors:	Saeed, Mamoon M, Saeed, Rashid A, Ali, Elmustafa Sayed, Mokhtar, Rania A, Khalifa, Othman Omran
Format:	Proceeding Paper
Language:	English
Published:	IEEE 2024
Subjects:	T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/114447/1/114447_Algorithm%20for%20resource%20allocation.pdf http://irep.iium.edu.my/114447/ https://ieeexplore.ieee.org/document/10652281
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id	my.iium.irep.114447
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spelling	my.iium.irep.1144472024-09-18T08:48:59Z http://irep.iium.edu.my/114447/ Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based Saeed, Mamoon M Saeed, Rashid A Ali, Elmustafa Sayed Mokhtar, Rania A Khalifa, Othman Omran T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering The emergence of the sixth generation (6G) wireless networks brings new challenges and opportunities for efficient computing offloading and resource allocation. This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G networks. The algorithm leverages the power of deep reinforcement learning to dynamically determine the optimal computing offloading decisions and resource allocation strategies. The Deep Reinforcement Learning-based DCORA algorithm for computation offloading and resource allocation is effective, as demonstrated by our simulations. When compared directly, the suggested DCORA algorithm performs 15% better than other baseline systems. IEEE 2024-09-04 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/114447/1/114447_Algorithm%20for%20resource%20allocation.pdf Saeed, Mamoon M and Saeed, Rashid A and Ali, Elmustafa Sayed and Mokhtar, Rania A and Khalifa, Othman Omran (2024) Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based. In: 9th International Conference on Mechatronics Engineering (ICOM 2024), 13th - 14th August 2024, Kuala Lumpur, Malaysia. https://ieeexplore.ieee.org/document/10652281 10.1109/ICOM61675.2024.10652281
institution	Universiti Islam Antarabangsa Malaysia
building	IIUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	International Islamic University Malaysia
content_source	IIUM Repository (IREP)
url_provider	http://irep.iium.edu.my/
language	English
topic	T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) T10.5 Communication of technical information TK Electrical engineering. Electronics Nuclear engineering Saeed, Mamoon M Saeed, Rashid A Ali, Elmustafa Sayed Mokhtar, Rania A Khalifa, Othman Omran Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
description	The emergence of the sixth generation (6G) wireless networks brings new challenges and opportunities for efficient computing offloading and resource allocation. This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G networks. The algorithm leverages the power of deep reinforcement learning to dynamically determine the optimal computing offloading decisions and resource allocation strategies. The Deep Reinforcement Learning-based DCORA algorithm for computation offloading and resource allocation is effective, as demonstrated by our simulations. When compared directly, the suggested DCORA algorithm performs 15% better than other baseline systems.
format	Proceeding Paper
author	Saeed, Mamoon M Saeed, Rashid A Ali, Elmustafa Sayed Mokhtar, Rania A Khalifa, Othman Omran
author_facet	Saeed, Mamoon M Saeed, Rashid A Ali, Elmustafa Sayed Mokhtar, Rania A Khalifa, Othman Omran
author_sort	Saeed, Mamoon M
title	Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
title_short	Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
title_full	Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
title_fullStr	Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
title_full_unstemmed	Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
title_sort	algorithm for resource allocation and computing offloading in 6g networks: deep reinforcement learning-based
publisher	IEEE
publishDate	2024
url	http://irep.iium.edu.my/114447/1/114447_Algorithm%20for%20resource%20allocation.pdf http://irep.iium.edu.my/114447/ https://ieeexplore.ieee.org/document/10652281
_version_	1811679641230901248
score	13.211869

Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based

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