Background and Motivation

In this work, we will focus on Low-Earth orbit (LEO) Earth observation satellites — satellites with orbital periods of < 128 min and with low eccentricity (i.e., near-circular orbits), resulting in altitude < 2000 km. We focus on LEO EO satellites because a) EO satellites are often placed in LEO orbit in order to improve the spatial resolution of the generated imagery, and b) The number and size of LEO EO satellite constellations has been increasing [48], in large part due to significant decreases in LEO satellite launch costs [58, 83] as well as due to emergence of new EO applications (Section 5).

Unlike the EO data generation rate, which is increasing rapidly, there is limited opportunity to increase RF downlink capacity [125]. As such, downlink data rates have increased less than data generation rates (Fig. 3). Several approaches have been proposed to deal with this downlink deficit. Lossless and high quality lossy compression can be used to decrease the number of bits needed to represent each pixel downlinked. More aggressively, data can be discarded — either not downlinked or not even generated. This is done commonly in practice (e.g., Dove does not image the ocean); prior work [54] also propose to do it via image processing (e.g., detect and discard images occluded by clouds). Our work does not focus on reducing the amount of EO data to be sent to the applications running on Earth; we move the applications themselves to space.

在本文中，我们将重点关注低地球轨道（Low-Earth orbit, LEO）地球观测卫星——即轨道周期小于128分钟、偏心率较低（即近圆形轨道），从而轨道高度低于2000公里的卫星。我们之所以关注LEO地球观测卫星，原因有二：

a) 为了提高生成图像的空间分辨率，EO卫星通常被部署在LEO轨道

b) LEO EO卫星星座的数量和规模一直在增长 [48]，这在很大程度上得益于LEO卫星发射成本的显著降低 [58, 83] 以及新兴EO应用的出现（第5节）

与快速增长的EO数据生成速率不同，射频（RF）下行链路容量的提升空间十分有限 [125]。因此，下行链路数据速率的增长速度已落后于数据生成速率（图3）

学术界已提出多种方法来应对这一下行链路瓶颈

• 无损压缩和高质量有损压缩可用于减少下行传输时每个像素所需的比特数
• 更为激进的方法是直接丢弃数据——要么不进行下行传输，要么甚至不生成数据。这在实践中很常见（例如，Dove卫星不拍摄海洋）；先前的工作 [54] 也提出通过图像处理技术来实现这一点（例如，检测并丢弃被云层遮挡的图像）

我们的工作重点并非减少需要发送给地面应用处理的EO数据量，而是将应用本身转移到太空

The closest related work is the deployment of HPE’s SpaceBorne and SpaceBorne-2 computers to the International Space Station (ISS). These computers have been used to compute on data generated in space which had historically been slow to downlink. For example, astronauts have used these computers to monitor their DNA for mutation due to radiation exposure. This decreased the amount of time needed to analyze astronaut DNA from 12 h (mostly in downlink time) to 6 min [144]. Unlike our work, the HPE ISS computers do not process EO data from EO satellites.

Another closely related work is by Orbits Edge [110], a start-up that is trying to build frames to send servers to outer space. Limited information is available about their design.

To the best of our knowledge, no prior work makes a quantitative case for SµDCs. Ours is also the first work to analyze the computation requirements for a SµDC, the associated communication bottlenecks, and the SµDC-communication co-design approaches to address the bottlenecks.

与本研究最相关的工作是慧与（HPE）公司在国际空间站（ISS）上部署的SpaceBorne和SpaceBor-2计算机。这些计算机被用于处理在太空中生成、但过去下行传输缓慢的数据。

例如，宇航员曾使用这些计算机监测其DNA因辐射暴露而发生的突变。这使得分析宇航员DNA所需的时间从12小时（主要为下行传输时间）缩短至6分钟 [144]。但与我们的工作不同，HPE在国际空间站的计算机并不处理来自其他EO卫星的地球观测数据。

另一项密切相关的工作来自 初创公司Orbits Edge [110]，该公司正尝试构建用于将服务器送往外太空的框架。 然而，关于其设计的公开信息非常有限。

据我们所知，此前没有任何工作为太空微数据中心（SµDCs）的建立提供定量论证。本文也是首个分析SµDC计算需求、相关的通信瓶颈，并提出解决这些瓶颈的SµDC与通信协同设计方法的研究。