Session
Weekday Session 11: Advanced Technologies II
Location
Utah State University, Logan, UT
Abstract
Time-to-insight is a critical measure in a number of satellite mission applications: detection and warning of fast-moving events like fires and floods, or identification and tracking of satellites or missiles, for example. Current data flows delay the time-to-insight on the order of minutes or hours, as all collected data must be downlinked in one or more contact windows, then transited over terrestrial networks to the location of the analytic software. Additionally, mission applications on spacecraft are often static: built prior to launch, they cannot rapidly adapt to changing needs based on these insights.
To reduce time-to-insight and provide a dynamic application update capability, Amazon Web Services (AWS), D-Orbit, and Unibap conducted a joint experiment in which we deployed AWS edge compute and network management software onto Unibap’s SpaceCloud® iX5 platform for edge computing in space, integrated onto a D-Orbit ION Satellite Carrier launched into low-earth orbit (LEO) in early 2022.
In this paper, we present the results of this experiment. We will discuss the software specifics and network management capabilities we developed to write mission applications and update those mission applications on-orbit, and detail the process of mission deployment and modification, communications latency, and data volume reduction. We will also discuss how the space and satellite community can use this capability to deploy new applications, performing complex tasks and reducing time-to-insight, to cloud-enabled satellites immediately without needing to wait for a new launch.
Extension of Cloud Computing to Small Satellites
Utah State University, Logan, UT
Time-to-insight is a critical measure in a number of satellite mission applications: detection and warning of fast-moving events like fires and floods, or identification and tracking of satellites or missiles, for example. Current data flows delay the time-to-insight on the order of minutes or hours, as all collected data must be downlinked in one or more contact windows, then transited over terrestrial networks to the location of the analytic software. Additionally, mission applications on spacecraft are often static: built prior to launch, they cannot rapidly adapt to changing needs based on these insights.
To reduce time-to-insight and provide a dynamic application update capability, Amazon Web Services (AWS), D-Orbit, and Unibap conducted a joint experiment in which we deployed AWS edge compute and network management software onto Unibap’s SpaceCloud® iX5 platform for edge computing in space, integrated onto a D-Orbit ION Satellite Carrier launched into low-earth orbit (LEO) in early 2022.
In this paper, we present the results of this experiment. We will discuss the software specifics and network management capabilities we developed to write mission applications and update those mission applications on-orbit, and detail the process of mission deployment and modification, communications latency, and data volume reduction. We will also discuss how the space and satellite community can use this capability to deploy new applications, performing complex tasks and reducing time-to-insight, to cloud-enabled satellites immediately without needing to wait for a new launch.
