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Latency Optimization for Computation Offloading with Hybrid NOMA-OMA Transmission
Liu,Lina1; Sun,Bo1; Wu,Yuan2,3; Tsang,Danny H.K.1
2021-01-29
Source PublicationIEEE Internet of Things Journal
ISSN2327-4662
Volume8Issue:8Pages:6677-6691
Abstract

The Internet of Things (IoT) platform is faced with critical challenges posed by the conflict between resource-hungry IoT applications and resource-constrained IoT devices. Mobile edge computing (MEC) provides a promising solution by allowing IoT devices to offload their computation to nearby edge servers to enable fast and energy-efficient data processing. In this paper, we study a scenario where two IoT users (IoT devices) offload their computation workloads to an edge server with hybrid non-orthogonal multiple access (NOMA)-orthogonal multiple access (OMA) transmission. The hybrid multiple access transmission incorporates three offloading methods, namely, hybrid NOMA, pure NOMA, and pure OMA. The offloading-method selection, together with user selection which determines the roles played by different IoT users in data transmission, comprises our offloading strategy, and is optimized to minimize the maximal offloading latency of the two IoT users. By exploiting the method of successive convex approximation (SCA), we design an efficient algorithm to solve the complicated non-convex problem and rigorously prove the convergence of our algorithm. Extensive numerical tests show that our scheme can always help IoT users to flexibly choose the best offloading strategy. Inspired by experimental observations, we analytically establish the criteria for the three offloading methods. We show that pure OMA transmission is never the best offloading method, except in some extreme cases that rarely occur in practice, while pure NOMA transmission is the most desirable offloading method in terms of latency minimization. We then propose detection approaches for the best offloading strategy with both offloading-method selection and user selection under certain system settings. The user selection is applied to avoid the pure OMA transmission and encourage the pure NOMA transmission.

KeywordApproximation Algorithms Computation Offloading Hybrid Noma-oma Transmission Internet Of Things Internet Of Things (Iot). Latency Minimization Minimization Noma Resource Management Servers Silicon Carbide
DOI10.1109/JIOT.2021.3055510
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000638402100044
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Scopus ID2-s2.0-85100465322
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorLiu,Lina
Affiliation1.Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China
2.Univ Macau, State Key Lab Internet Things Smart City, Macau, Peoples R China
3.Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China
Recommended Citation
GB/T 7714
Liu,Lina,Sun,Bo,Wu,Yuan,et al. Latency Optimization for Computation Offloading with Hybrid NOMA-OMA Transmission[J]. IEEE Internet of Things Journal,2021,8(8):6677-6691.
APA Liu,Lina,Sun,Bo,Wu,Yuan,&Tsang,Danny H.K..(2021).Latency Optimization for Computation Offloading with Hybrid NOMA-OMA Transmission.IEEE Internet of Things Journal,8(8),6677-6691.
MLA Liu,Lina,et al."Latency Optimization for Computation Offloading with Hybrid NOMA-OMA Transmission".IEEE Internet of Things Journal 8.8(2021):6677-6691.
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