부산대학교 도서관

China possesses vast and valuable natural resources in its expansive cold and arid regions, but the natural environment is harsh. Field stations and observation systems primarily emphasize in-station observations and research. Nevertheless, these systems face challenges such as limited energy resources, inability to cope with the dynamic nature of the environment, and obstacles in conducting extensive and large-scale scientific research. To advance the automation level of field observation data, enhance real-time data transmission performance, and bolster the adaptive capabilities of field observation instrument networks (FOINs), a novel method named a routing protocol based on multiobjective mayfly optimization algorithm (MMA) for solar energy dynamical supply of FOIN (DSFOI-MMA) is proposed in this article. The proposed protocol first designs an energy harvesting model based on the dynamic nature of solar energy to ensure energy supply for low-energy nodes in the network, and then dynamically elects the optimal cluster head (CH) via MMA. Second, the idea of virtual complete graphs is introduced to construct inter-cluster transmission paths. Finally, the MATLAB simulation platform is utilized to validate the effectiveness of the DSFOI-MMA. Extensive experiments and analyses have been performed to compare with existing major approaches in terms of network lifetime, number of CHs, and so on. The results demonstrate the excellent performance of the developed protocol, which enhances the automation of monitoring data and provides a reliable guarantee of experimental data for in-depth scientific research and development in cold and arid regions.