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Article

Offloading Strategy for Forest Monitoring Network Based on Improved Beetle Optimization Algorithm

1
School of Computer Science and Engineering, Guilin University of Technology, Guilin 541004, China
2
Guangxi Key Laboratory of Embedded Technology and Intelligent System, Guilin 541004, China
3
Guangxi Forestry Research Institute, Nanning 530002, China
*
Author to whom correspondence should be addressed.
Symmetry 2024, 16(12), 1569; https://doi.org/10.3390/sym16121569
Submission received: 20 October 2024 / Revised: 13 November 2024 / Accepted: 18 November 2024 / Published: 23 November 2024
(This article belongs to the Special Issue Symmetry and Asymmetry in Embedded Systems)

Abstract

In forest monitoring networks, the computational capabilities of sensors cannot meet the latency requirements for complex tasks, and the limited battery capacity of these sensors hinders the long-term execution of monitoring tasks. Mobile edge computing (MEC) acts as an effective solution for this issue by offloading tasks to edge servers, significantly reducing both task latency and energy consumption. However, the computational capacity of MEC servers and the bandwidth in the system are limited, and the communication environment in forested areas is complex. To simulate the complexity of the forest communication environment, we incorporate empirical path loss and multipath fading into the calculation of signal transmission rates. The computational offloading problem is then converted into a minimum-cost optimization problem with multiple constraints related to energy consumption and latency, which we formulate as an NP-hard problem. We propose a dung beetle optimization (DBO) strategy for computational offloading, enhancing it with an improved circle chaotic mapping, a dimension decomposition strategy, and Cauchy disturbance. This algorithm has the beauty of symmetry in the search range, and the symmetrical features can comprehensively search for existing solutions. Experimental results demonstrate that the improved dung beetle optimization algorithm (IDBO) achieves better convergence, lower complexity, and superior optimization outcomes compared to local offloading strategies and other metaheuristic algorithms, confirming the effectiveness of the proposed algorithm and ensuring the service quality of the forest monitoring network.
Keywords: forest monitoring networks; mobile edge computing; computation offloading; offloading cost optimization; dung beetle optimization algorithm; symmetrical features forest monitoring networks; mobile edge computing; computation offloading; offloading cost optimization; dung beetle optimization algorithm; symmetrical features

Share and Cite

MDPI and ACS Style

Cheng, X.; Lu, X.; Deng, Y.; Lu, Q.; Kang, Y.; Tang, J.; Shi, Y.; Zhao, J. Offloading Strategy for Forest Monitoring Network Based on Improved Beetle Optimization Algorithm. Symmetry 2024, 16, 1569. https://doi.org/10.3390/sym16121569

AMA Style

Cheng X, Lu X, Deng Y, Lu Q, Kang Y, Tang J, Shi Y, Zhao J. Offloading Strategy for Forest Monitoring Network Based on Improved Beetle Optimization Algorithm. Symmetry. 2024; 16(12):1569. https://doi.org/10.3390/sym16121569

Chicago/Turabian Style

Cheng, Xiaohui, Xiangang Lu, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, and Junyu Zhao. 2024. "Offloading Strategy for Forest Monitoring Network Based on Improved Beetle Optimization Algorithm" Symmetry 16, no. 12: 1569. https://doi.org/10.3390/sym16121569

APA Style

Cheng, X., Lu, X., Deng, Y., Lu, Q., Kang, Y., Tang, J., Shi, Y., & Zhao, J. (2024). Offloading Strategy for Forest Monitoring Network Based on Improved Beetle Optimization Algorithm. Symmetry, 16(12), 1569. https://doi.org/10.3390/sym16121569

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