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Article

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

1
Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Build Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
2
Department of Electronics Engineering, Yarmouk University, Irbid 21163, Jordan
3
Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, Seoul 05006, Korea
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Manuel Fernandez-Veiga
Sustainability 2021, 13(21), 12112; https://doi.org/10.3390/su132112112
Received: 10 August 2021 / Revised: 28 September 2021 / Accepted: 5 October 2021 / Published: 2 November 2021
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%. View Full-Text
Keywords: mobile edge computing; NOMA; full offloading; partial offloading mobile edge computing; NOMA; full offloading; partial offloading
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MDPI and ACS Style

Andrawes, A.; Nordin, R.; Albataineh, Z.; Alsharif, M.H. Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios. Sustainability 2021, 13, 12112. https://doi.org/10.3390/su132112112

AMA Style

Andrawes A, Nordin R, Albataineh Z, Alsharif MH. Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios. Sustainability. 2021; 13(21):12112. https://doi.org/10.3390/su132112112

Chicago/Turabian Style

Andrawes, Admoon, Rosdiadee Nordin, Zaid Albataineh, and Mohammed H. Alsharif. 2021. "Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios" Sustainability 13, no. 21: 12112. https://doi.org/10.3390/su132112112

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