Energy-Efficient Online Data Sensing and Processing in Wireless Powered Edge Computing Systems

Li, Xian; Bi, Suzhi; Zheng, Yuan; Wang, Hui

doi:10.1109/tcomm.2022.3186718

Cited by 11 publications

(3 citation statements)

References 29 publications

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“…cycles [17,18]. We consider 15 types of power services and divide them into low, medium, and high levels according to their importance, which are shown as follows.…”

Section: Simulation Resultsmentioning

confidence: 99%

Edge processing mechanism for high-frequency information acquisition in low-voltage distribution grid

Lu,

Zhang,

Zhang

et al. 2023

5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023)

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To improve the performance of high-frequency information acquisition data processing and meet the differentiated power service requirements in low-voltage distribution grid, this paper first investigates an edge processing architecture for high-frequency information acquisition in low-voltage distribution grid. Then, an edge processing mechanism for high-frequency information acquisition is proposed to optimize the high-frequency information acquisition data distribution strategy and communication and computation resource allocation strategies. Simulation results demonstrate that the proposed mechanism achieves better data processing performances compared with traditional data processing mechanism

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“…cycles [17,18]. We consider 15 types of power services and divide them into low, medium, and high levels according to their importance, which are shown as follows.…”

Section: Simulation Resultsmentioning

confidence: 99%

Edge processing mechanism for high-frequency information acquisition in low-voltage distribution grid

Lu,

Zhang,

Zhang

et al. 2023

5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023)

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show abstract

“…In MEC systems, according to the separability of tasks, the task offloading can be classified into two categories: inseparable task offloading [10]- [12] and separable task offloading [13], [14]. In the inseparable task offloading, each user attempts to offload the entire task to the MEC server.…”

Section: Introductionmentioning

confidence: 99%

“…In the separable task offloading, each user offloads several portions of the task to the servers while locally executing the remaining portion, in order to fully utilize the local computation resource of users and relief the burden of task offloading. For users supported by single server, an enhanced online Lyapunov optimization algorithm was proposed to maximize the long-term average data rate [13]. Further, for users supported by multiple servers, the long-term energy consumption of all users was minimized by an enhanced deep reinforcement learning approach [14].…”

Section: Introductionmentioning

confidence: 99%

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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Task execution latency minimization for energy-sensitive IoTs in wireless powered mobile edge computing: A DRL-based method

Li,

Xu,

Liu

et al. 2024

Computer Networks

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Energy-Efficient Online Data Sensing and Processing in Wireless Powered Edge Computing Systems

Cited by 11 publications

References 29 publications

Edge processing mechanism for high-frequency information acquisition in low-voltage distribution grid

Edge processing mechanism for high-frequency information acquisition in low-voltage distribution grid

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

Task execution latency minimization for energy-sensitive IoTs in wireless powered mobile edge computing: A DRL-based method

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