Enhancing NOMA-MEC Based Intelligent Farming: Performance Analysis and HSBOO Optimization
In intelligent farming systems, Internet of Farming Things (IoFT) devices are now broadly applied and play a significant role in agricultural science. Due to the shortage of computation, battery and storage capability of terminal IoFT devices, certain tasks must be offloaded to multiaccess edge comp...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Communications Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11025819/ |
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| Summary: | In intelligent farming systems, Internet of Farming Things (IoFT) devices are now broadly applied and play a significant role in agricultural science. Due to the shortage of computation, battery and storage capability of terminal IoFT devices, certain tasks must be offloaded to multiaccess edge computing (MEC) server for processing. Furthermore, non-orthogonal multiple access (NOMA) approach is introduced to address the issue caused by the resource constraint of wireless transmission. This article examines the performance and optimization of NOMA-MEC based intelligent farming system. To assess the system performance and examine the influence of network attributes on intelligent farming system, the precise closed expression of the end-to-end delay outage probability (DOP) under Nakagami-m channel is derived. Then, the hybrid secretary bird osprey optimization (HSBOO) algorithm is proposed to analyse an optimization problem whose goal is to minimize the DOP by optimizing the task and power allocation. The outcomes demonstrate that the suggested HSBOO algorithm can considerably enhance the throughput by 11.05% over the NOMA-MEC system. |
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| ISSN: | 2644-125X |