摘要
Driven by the widespread applications of Space-Air-Ground Integrated Networks (SAGINs) in a number of practical fields, the volume of space data grows rapidly. However, the large volume of space data in SAGINs is typically intractable to be offloaded from space to the ground under the high dynamic network topology and the stochastic data arrivals. Furthermore, most nodes in SAGINs are battery-powered and energy-constrained, thereby implying that energy consumption becomes one major bottleneck for data offloading. Towards this end, this paper studies online joint data offloading and power control in SAGINs to maximize long-term time-averaged data offloaded amount under the constraints of average energy consumption. First, we propose a novelty Two-timescale Time-Expanded Graph (TTEG) to characterize the rapid change of the network topology in large-timescale slots and capture the stochastic data arrivals in small-timescale slots. Based the TTEG model, we formulate a stochastic optimization problem and transform it into a series of per-time-slot subproblems to obtain an efficient online solution. Through theoretical analyses, we show that the performance gap with optimal solution is bounded. Finally, extensive simulations demonstrate that the maximum performance gap of our proposed online solution to the optimal solution is less than 2% in a low computation cost.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 18126-18141 |
| 页数 | 16 |
| 期刊 | IEEE Transactions on Wireless Communications |
| 卷 | 23 |
| 期 | 12 |
| DOI | |
| 出版状态 | 已出版 - 2024 |
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