Summary and Conclusion

In this work, we observe that future EO satellites will generate so much data that this data cannot be transmitted to Earth due to limited capacity of communication that exists between space and Earth. We showed that conventional data reduction techniques such as compression [130] and early discard [54] do not solve this problem, nor does a direct enhancement of today’s RF-based infrastructure [136, 153] for space-Earth communication. We explored an unorthodox solution instead - moving to space the computation that would have happened on the ground. This alleviates the need for data transfer to Earth. We analyzed ten non-longitudinal RGB and hyperspectral image processing Earth observation applications for their computation and power requirements and discovered that these requirements could not be met by the small satellites that dominate today’s EO missions. We made a case for space microdatacenters (SµDCs) - computational satellites tasked to support in-space computation of EO data. We showed that one 4KW space microdatacenter can support the computation need of a majority of applications. To address the communication bottleneck between EO satellites and SµDCs, we proposed three space microdatacentercommunication co-design strategies – 𝑘 −𝑙𝑖𝑠𝑡-based network topology, microdatacenter splitting, and moving space microdatacenters to geostationary orbit. These techniques enable effective usage of SµDCs.