Abstract
In this paper we construct a double layer satellite network and let MEO satellites carry computing servers to execute computation tasks generated by LEO satellites. The main purpose is to find a task offloading scheme and resource allocation strategy to minimize the energy consumption of the dynamic network which is formulated as a mixed-integer programming problem. To solve it efficiency, we research a suboptimal resource allocation and computation offloading scheme. Specifically, the original problem is divided into three subproblems. The first subproblem is a convex problem which is easy to solve it. Then for the next subproblem, we propose a terminal satellites and edge satellites matching strategy (TEMS). For the last one, random adjustment execution algorithm is applied. Finally, the simulation results have be given to verify the effectiveness of proposed algorithm.
This work was supported partially by National Natural Science Foundation of China (Grant Nos. 61971156, 61801144), Shandong Provincial Natural Science Foundation, China (Grant Nos. ZR2019QF003, ZR2019MF035, ZR2020MF141), the Fundamental Research Funds for the Central Universities, China (Grant No. HIT.NSRIF.2019081).
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Zhu, W., Yang, W., Liu, G. (2023). Server Selection and Resource Allocation for Energy Minimization in Satellite Edge Computing. In: Li, A., Shi, Y., **, L. (eds) 6GN for Future Wireless Networks. 6GN 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 505. Springer, Cham. https://doi.org/10.1007/978-3-031-36014-5_12
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DOI: https://doi.org/10.1007/978-3-031-36014-5_12
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