Optimal Download of Dynamically Generated Data by Using ISL Offloading in LEO Networks

Jiajing Wang, N. Yu, Hejiao Huang, X. Jia
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引用次数: 1

Abstract

With the growing demand for satellite network technology in military and commercial applications, a large number of LEO(Low Earth Orbit) satellites have been launched in various countries around the world. One of the most important tasks is to download the data collected by these satellites to the Earth Stations(ESs) for processing. Previous research efforts have focused on how to download satellite-collected data to ESs. They didn't consider the situation that the satellites continuously collect data when downloading data. In this paper, our goal is to optimize the data download from the satellites to the ES in the case of dynamic collection of satellite data. We use inter-satellite links (ISLs) to offload data from heavily loaded satellites to the light ones. We build a topology map based on the interaction time between satellites and the interaction time between the satellite and the ES, and allocate the download time to the satellite carrying the largest amount of data. Then, the time slice is dynamically divided and the inter-satellite scheduling is determined by a way of classifying the idle satellites. Finally, the maximum flow algorithm is applied to determine the specific inter-satellite transmission scheme. In this way, the ES idle time is minimized. Simulations results show that our solution can greatly improve the data download efficiency from the satellites to the ES.
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在LEO网络中利用ISL卸载实现动态生成数据的最优下载
随着军事和商业应用对卫星网络技术需求的不断增长,世界各国发射了大量近地轨道卫星。最重要的任务之一是将这些卫星收集的数据下载到地面站进行处理。以前的研究工作集中在如何将卫星收集的数据下载到ESs上。他们没有考虑到卫星在下载数据时持续收集数据的情况。在本文中,我们的目标是在卫星数据动态采集的情况下,优化从卫星到ES的数据下载。我们使用卫星间链路(ISLs)将数据从负载较重的卫星上卸载到负载较轻的卫星上。我们根据卫星之间的交互时间和卫星与ES之间的交互时间构建了拓扑图,并将下载时间分配给承载数据量最大的卫星。然后,通过对空闲卫星进行分类,动态划分时间片,确定卫星间调度;最后,应用最大流量算法确定卫星间传输的具体方案。通过这种方式,ES空闲时间被最小化。仿真结果表明,该方案可以大大提高从卫星到ES的数据下载效率。
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