Huang, HuaweiGuo, SongLiang, WeifaWang, Kun2024-02-16May 20-24978-1-5386-4328-0http://hdl.handle.net/1885/313677As the critical supplementary to terrestrial communication networks, the low-earth-orbit (LEO) satellite based communication networks regain growing attentions in recent few years. In this paper, we focus on data gathering for geo- distributed Internet-of-Things (IoT) networks via LEO satellites. Normally, the power supply in IoT data-gathering gateways is a bottleneck resource that constrains the network throughput. Thus, the challenge is how to upload data from IoT gateways to LEO satellites under dynamic uplinks in an energy-efficient way. To address this problem, we first formulate a novel optimization problem, and then propose an online algorithm for green data-uploading in geo-distributed IoT networks. In the proposed framework, we aim to jointly maximize the network throughput and minimize the energy consumption at gateways, while avoiding the buffer overflow at gateways. We finally evaluate the performance of the proposed algorithm through simulations using both real-world and synthetic traces. The simulation results demonstrate that the proposed approach can achieve high efficiency on the power consumption and significantly reduce queue backlogs compared with a benchmark using greedy policy.This work is partially supported by Strategic Information and Communications R&D Promotion Programme (SCOPE No.162302008), MIC, Japan, and NSFC (61572262).application/pdfen-AU© 2018 IEEE201810.1109/ICC.2018.84225222022-10-02