Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios

The development of mobile edge computing (MEC) is expected to offer better performance in mobile communications than the current cloud computing architecture. MEC involves offering the closest access to the data source or physical mobile network environment. The network services are able to respond...

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Autores principales:	Admoon Andrawes, Rosdiadee Nordin, Zaid Albataineh, Mohammed H. Alsharif
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	mobile edge computing NOMA full offloading partial offloading Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/67794f6baa8549598a3fda6180c94489
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id	oai:doaj.org-article:67794f6baa8549598a3fda6180c94489
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spelling	oai:doaj.org-article:67794f6baa8549598a3fda6180c944892021-11-11T19:44:40ZSustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios10.3390/su1321121122071-1050https://doaj.org/article/67794f6baa8549598a3fda6180c944892021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/12112https://doaj.org/toc/2071-1050The development of mobile edge computing (MEC) is expected to offer better performance in mobile communications than the current cloud computing architecture. MEC involves offering the closest access to the data source or physical mobile network environment. The network services are able to respond faster, thus satisfying the demands of the mobile network industry when deploying various potential business applications in real-time. Since the harvested mobile data are transferred to the edge server to make calculations, data transfers and faults in the mobile network can be swiftly pinpointed and removed accurately. Nevertheless, there are still problems in the practical application of the systems, specifically in reducing delays and lessening energy consumption. Because of non-orthogonal multiple access (NOMA) superior spectrum efficiencies, it is best to combine NOMA with MEC for simultaneous support of multiple access for end users, thus reducing transmission latencies and lowering energy consumption. Combining MEC and NOMA would offer many advantages, including superior energy savings, reductions in latency, massive connectivity, and the potential of combining with additional transmission technologies, such as millimetre-wave (mmWave) and M-MIMO. In this paper, designing wireless resource allocation is crucial for an economically viable low-latency wireless network, which can be realised using the Karush–Kuhn–Tucker (KKT) approach to obtain the optimal solution for partial and full offloading network traffic scenarios to minimize the total latency of the MEC network. The convergence and performance for orthogonal multiple access (OMA), pure-NOMA (P-NOMA), and hybrid-NOMA (H-NOMA) are also compared under different network traffic offloading scenarios. The significant results from this study showed the convergence of the optimal resource allocation in the case of full and partial offloading. The results demonstrated that the P-NOMA reduces the total offloading delay by about 11%.Admoon AndrawesRosdiadee NordinZaid AlbatainehMohammed H. AlsharifMDPI AGarticlemobile edge computingNOMAfull offloadingpartial offloadingEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12112, p 12112 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	mobile edge computing NOMA full offloading partial offloading Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	mobile edge computing NOMA full offloading partial offloading Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Admoon Andrawes Rosdiadee Nordin Zaid Albataineh Mohammed H. Alsharif Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios
description	The development of mobile edge computing (MEC) is expected to offer better performance in mobile communications than the current cloud computing architecture. MEC involves offering the closest access to the data source or physical mobile network environment. The network services are able to respond faster, thus satisfying the demands of the mobile network industry when deploying various potential business applications in real-time. Since the harvested mobile data are transferred to the edge server to make calculations, data transfers and faults in the mobile network can be swiftly pinpointed and removed accurately. Nevertheless, there are still problems in the practical application of the systems, specifically in reducing delays and lessening energy consumption. Because of non-orthogonal multiple access (NOMA) superior spectrum efficiencies, it is best to combine NOMA with MEC for simultaneous support of multiple access for end users, thus reducing transmission latencies and lowering energy consumption. Combining MEC and NOMA would offer many advantages, including superior energy savings, reductions in latency, massive connectivity, and the potential of combining with additional transmission technologies, such as millimetre-wave (mmWave) and M-MIMO. In this paper, designing wireless resource allocation is crucial for an economically viable low-latency wireless network, which can be realised using the Karush–Kuhn–Tucker (KKT) approach to obtain the optimal solution for partial and full offloading network traffic scenarios to minimize the total latency of the MEC network. The convergence and performance for orthogonal multiple access (OMA), pure-NOMA (P-NOMA), and hybrid-NOMA (H-NOMA) are also compared under different network traffic offloading scenarios. The significant results from this study showed the convergence of the optimal resource allocation in the case of full and partial offloading. The results demonstrated that the P-NOMA reduces the total offloading delay by about 11%.
format	article
author	Admoon Andrawes Rosdiadee Nordin Zaid Albataineh Mohammed H. Alsharif
author_facet	Admoon Andrawes Rosdiadee Nordin Zaid Albataineh Mohammed H. Alsharif
author_sort	Admoon Andrawes
title	Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios
title_short	Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios
title_full	Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios
title_fullStr	Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios
title_full_unstemmed	Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios
title_sort	sustainable delay minimization strategy for mobile edge computing offloading under different network scenarios
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/67794f6baa8549598a3fda6180c94489
work_keys_str_mv	AT admoonandrawes sustainabledelayminimizationstrategyformobileedgecomputingoffloadingunderdifferentnetworkscenarios AT rosdiadeenordin sustainabledelayminimizationstrategyformobileedgecomputingoffloadingunderdifferentnetworkscenarios AT zaidalbataineh sustainabledelayminimizationstrategyformobileedgecomputingoffloadingunderdifferentnetworkscenarios AT mohammedhalsharif sustainabledelayminimizationstrategyformobileedgecomputingoffloadingunderdifferentnetworkscenarios
_version_	1718431413101920256

Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios

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