Cooperative NOMA-MEC With Helper Scheduling

Ren, Mengmeng; Chen, Jian; He, Bingtao; Wu, Keyu; Zhou, Yuchen; Xue, Xuan; Yang, Long

doi:10.1109/lcomm.2022.3165847

Cited by 9 publications

(13 citation statements)

References 16 publications

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“…The formulated optimization problem (i.e., problem ( 23)) is a mixed-integer nonlinear programming problem due to the non-convex objective function and non-convex constraints (11), (23g), (23h), (23i), and (23j). To tackle this challenging problem (23), we equivalently reformulate it as follows.…”

Section: Equivalent Problem Reformulationmentioning

confidence: 99%

“…Therefore, the continuous variables and 0-1 variables in original problem (23) can be jointly optimized by solving DUARA problem (25).…”

Section: Equivalent Problem Reformulationmentioning

confidence: 99%

“…Compared with the helper-assisted OMA-MEC, the helper-assisted NOMA-MEC can achieve higher spectral efficiency and lower offloading/computing delay [15]- [18]. More recently, the helperassisted NOMA-MEC has been investigated with using a single helper [20], [21] or multiple helpers [22], [23]. For the single-user NOMA-MEC assisted by only one helper, the minimization of energy consumption was investigated in [20] and [21].…”

Section: Introductionmentioning

confidence: 99%

“…When multiple helpers are available, an interior-point-based algorithm was proposed in [22] to maximize the offloading data of one task-driven user. In [23], an adaptive computing strategy with a helper scheduling scheme was proposed, in which one helper is adaptively scheduled from multiple helpers to assist task offloading.…”

Section: Introductionmentioning

confidence: 99%

“…From above works [20]- [23] on the helper-assisted NOMA-MEC, it can be observed that the helper-assisted task offloading was investigated for only a typical user. However, in multiuser NOMA-MEC systems, it is very likely that some active users require computing services at the same time, indicating that their tasks need to be offloaded/executed simultaneously.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Energy-Delay Tradeoff in Device-Assisted NOMA MEC Systems: A Matching-Based Algorithm

Ren

Chen

Zhou

et al. 2021

2021 IEEE Wireless Communications and Networking Conference (WCNC)

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This paper designs a helper-assisted resource allocation strategy in non-orthogonal multiple access (NOMA)enabled mobile edge computing (MEC) systems, in order to guarantee the quality of service (QoS) of the energy/delaysensitive user equipments (UEs). To achieve a tradeoff between the energy consumption and the delay, we introduce a novel performance metric, called energy-delay tradeoff, which is defined as the weighted sum of energy consumption and delay. The joint optimization of user association, resource block (RB) assignment, power allocation, task assignment, and computation resource allocation is formulated as a mixed-integer nonlinear programming problem with the aim of minimizing the maximal energy-delay tradeoff. Due to the non-convexity of the formulated problem with coupled and 0-1 variables, this problem cannot be directly solved with polynomial complexity. To tackle this challenge, we first decouple the formulated problem into a power allocation, task assignment and computation resource allocation (PATACRA) subproblem. Then, with the solution obtained from the PATACRA subproblem, we equivalently reformulate the original problem as a discrete user association and RB assignment (DUARA) problem. For the PATACRA subproblem, an iterative parametric convex approximation (IPCA) algorithm is proposed. Then, based on the solution obtained from the PATACRA subproblem, we first model the DUARA problem as a four-sided matching problem, and then propose a low-complexity four-sided UE-RB-helperserver matching (FS-URHSM) algorithm. Theoretical analysis demonstrates that the proposed algorithms are guaranteed to converge to stable solutions with polynomial complexity. Finally, simulation results are provided to show the superior performance of our proposed algorithm in terms of the energy consumption and the delay.

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Section: Equivalent Problem Reformulationmentioning

confidence: 99%

“…Therefore, the continuous variables and 0-1 variables in original problem (23) can be jointly optimized by solving DUARA problem (25).…”

Section: Equivalent Problem Reformulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Energy-Delay Tradeoff in Device-Assisted NOMA MEC Systems: A Matching-Based Algorithm

Ren

Chen

Zhou

et al. 2021

2021 IEEE Wireless Communications and Networking Conference (WCNC)

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Latency optimization of task offloading in NOMA‐MEC systems

et al. 2022

Self Cite

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This paper investigates low‐latency offloading strategy in a non‐orthogonal multiple access aided mobile edge computing (NOMA‐MEC) system consisting of K edge servers, one mobile user and one cloud server. An intelligent edge server selection strategy (IESSS) based on Markov decision process (MDP) is proposed to select an edge server, in order to reduce the task completion latency of this system. When an edge server is selected by the proposed IESSS, a joint optimization problem of power allocation and task scheduling factors is formulated to minimize the task completion latency of the hybrid NOMA‐MEC system. To solve the formulated non‐convex optimization problem with coupled variables, a low‐complexity adaptive power‐task resource allocation iterative (APTRAI) algorithm is proposed. Simulation results demonstrate the advantages of the proposed IESSS and verify the convergence and time complexity of the proposed APTRAI algorithm.

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Joint Task Assignment, Power Allocation and Node Grouping for Cooperative Computing in NOMA-mmWave Mobile Edge Computing

Khazali,

Bozorgchenani,

Tarchi

et al. 2023

IEEE Access

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In this paper, we investigate the cooperation of idle computation resources of nearby mobile devices in mobile edge computing (MEC) systems, in which each mobile device jointly offloads computation tasks to a MEC node and a nearby mobile device by employing non-orthogonal multiple access (NOMA) in a millimeter-wave (mmWave) heterogeneous network. In this setup, the nearby device acts as a helper by performing local computation and offloading data simultaneously to the MEC system. We formulate an optimization problem for joint taSk assignmenT, poweR allOcation and Node Grouping (STRONG) aiming to minimize the energy consumption of devices (i.e., user and helper devices). To tackle this problem, we present a two-step solution. First, we adopt a low complexity search-based algorithm for both helper and MEC server selection. Next, considering the non-convex nature of the energy minimization problem, we develop algorithms that provide sub-optimal solutions for power allocation to the helper and MEC server, as well as the offloading task ratios between them. Numerical results are provided to validate the effectiveness of our proposed algorithms. The results not only validate the efficiency of our approach but also demonstrate the superiority of our cooperative NOMA-based MEC scenario compared to methods without cooperation and other cooperation-based scenarios.

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Cooperative NOMA-MEC With Helper Scheduling

Cited by 9 publications

References 16 publications

Energy-Delay Tradeoff in Device-Assisted NOMA MEC Systems: A Matching-Based Algorithm

Energy-Delay Tradeoff in Device-Assisted NOMA MEC Systems: A Matching-Based Algorithm

Latency optimization of task offloading in NOMA‐MEC systems

Joint Task Assignment, Power Allocation and Node Grouping for Cooperative Computing in NOMA-mmWave Mobile Edge Computing

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