A Decision Framework for Allocation of Constellation-Scale Mission Compute Functionality to Ground and Edge Computing

This paper explores constellation-scale architectural trades, highlights dominant factors, and presents a decision framework for migrating or sharing mission compute functionality between ground and space segments. Over recent decades, sophisticated logic has been developed for scheduling and tasking of space assets, as well as processing and exploitation of satellite data, and this software has been traditionally hosted in ground computing. Current efforts exist to migrate this software to ground cloud-based services. The option and motivation to host some of this logic “at the edge” within the space segment has arisen as space assets are proliferated, are interlinked via transport networks, and are networked with multi-domain assets. Examples include edge-based Battle Management, Command, Control, and Communications (BMC3) being developed by the Space Development Agency and future onboard computing for commercial constellations. Edge computing pushes workload, computation, and storage closer to data sources and onto devices at the edge of the network. Potential benefits of edge computing include increased speed of response, system reliability, robustness to disrupted networks, and data security. Yet, space-based edge nodes have disadvantages including power and mass limitations, constant physical motion, difficulty of physical access, and potential vulnerability to attacks. This paper presents a structured decision framework with justifying rationale to provide insights and begin to address a key question of what mission compute functionality should be allocated to the space-based edge , and under what mission or architectural conditions, versus to conventional ground-based systems. The challenge is to identify the Pareto-dominant trades and impacts to mission success. This framework will not exhaustively address all missions, architectures, and CONOPs, however it is intended to provide generalized guidelines and heuristics to support architectural decision-making. Via effects-based simulation and analysis, a set of hypotheses about ground- and edge-based architectures are evaluated and summarized along with prior research. Results for a set of key metrics and decision drivers show that edge computing for specific functionality is quantitatively valuable, especially for interoperable, multi-domain, collaborative assets

Proliferated LEO Autonomy Architecture for Capability with Scalability

A next generation space architecture focused on proliferated low-Earth Orbit (p-LEO) constellations holds the promise of improved situational awareness, responsiveness, and resiliency. A variety of proliferated space constellation efforts are underway in the National Security Space Arena, all demanding innovations in ubiquitous satellite command, control, and communications. Whether communications, science, or defense missions, the expansion into PLEO constellations drives new demands upon autonomy, software, and communications architectures. Previous groundbreaking autonomy work was performed on the Deep Space 1 mission, which eventually led to NASA Mars and Earth Observing-1 autonomy. In Autonomous Rendezvous, Proximity Operations, and Docking (ARPOD), Defense Advanced Research Projects Agency (DARPA)\u27s Orbital Express and the Air Force XSS-10 mission helped establish the state of the art. While similarities exist, mission autonomy for these individual spacecraft missions fundamentally differs from PLEO constellations in their demands and constraints

Sagittarius A* Small Satellite Mission: Capabilities and Commissioning Preview

SSCI is leading a Defense Advanced Research Projects Agency (DARPA)-funded team launching a mission in June 2021, dubbed Sagittarius A*, to demonstrate key hardware and software technologies for on-orbit autonomy, to provide a software testbed for on-orbit developmental test & autonomous mission operations, and to reduce risk for future constellation-level mission autonomy and operations. In this paper, we present the system CONOPs and capabilities, system architectures, flight and ground software development status, and initial commissioning status. The system will fly on Loft Orbital’s YAM-3 shared LEO satellite mission, and includes SSCI’s onboard autonomy software suite running on an Innoflight CFC-400 processor with onboard Automatic Target Recognition (ATR). The autonomy payload has attitude control authority over the spacecraft bus and command authority of the imaging payload, and performs fully-autonomous onboard request handling, resource & task allocation, collection execution, ATR, and detection downlinking. The system is capable of machine-to -machine tip-and-cue from offboard cueing sources via cloud-based integrations. Requests for mission data are submitted to the satellite throughout its orbit from a tactical user level via a smartphone application, and ISR data products are downlinked and displayed at the tactical level on an Android Tactical Assault Kit (ATAK) smartphone. Follow-on software updates can be sent to the autonomy suite as over-the-air updates for on-orbit testing at any time during the on-orbit life of the satellite. Communications include GlobalStar inter-satellite communications for low rate task and status monitoring, and ground station links for payload data downloads. Planned demonstrations and opportunities will be discussed

Fluidic Microactuation of Flexible Electrodes for Neural Recording

Soft and conductive nanomaterials like carbon nanotubes, graphene, and nanowire scaffolds have expanded the family of ultraflexible microelectrodes that can bend and flex with the natural movement of the brain, reduce the inflammatory response, and improve the stability of long-term neural recordings. However, current methods to implant these highly flexible electrodes rely on temporary stiffening agents that temporarily increase the electrode size and stiffness thus aggravating neural damage during implantation, which can lead to cell loss and glial activation that persists even after the stiffening agents are removed or dissolve. A method to deliver thin, ultraflexible electrodes deep into neural tissue without increasing the stiffness or size of the electrodes will enable minimally invasive electrical recordings from within the brain. Here we show that specially designed microfluidic devices can apply a tension force to ultraflexible electrodes that prevents buckling without increasing the thickness or stiffness of the electrode during implantation. Additionally, these “fluidic microdrives” allow us to precisely actuate the electrode position with micron-scale accuracy. To demonstrate the efficacy of our fluidic microdrives, we used them to actuate highly flexible carbon nanotube fiber (CNTf) microelectrodes for electrophysiology. We used this approach in three proof-of-concept experiments. First, we recorded compound action potentials in a soft model organism, the small cnidarian <i>Hydra</i>. Second, we targeted electrodes precisely to the thalamic reticular nucleus in brain slices and recorded spontaneous and optogenetically evoked extracellular action potentials. Finally, we inserted electrodes more than 4 mm deep into the brain of rats and detected spontaneous individual unit activity in both cortical and subcortical regions. Compared to syringe injection, fluidic microdrives do not penetrate the brain and prevent changes in intracranial pressure by diverting fluid away from the implantation site during insertion and actuation. Overall, the fluidic microdrive technology provides a robust new method to implant and actuate ultraflexible neural electrodes

Fluidic Microactuation of Flexible Electrodes for Neural Recording

Soft and conductive nanomaterials like carbon nanotubes, graphene, and nanowire scaffolds have expanded the family of ultraflexible microelectrodes that can bend and flex with the natural movement of the brain, reduce the inflammatory response, and improve the stability of long-term neural recordings. However, current methods to implant these highly flexible electrodes rely on temporary stiffening agents that temporarily increase the electrode size and stiffness thus aggravating neural damage during implantation, which can lead to cell loss and glial activation that persists even after the stiffening agents are removed or dissolve. A method to deliver thin, ultraflexible electrodes deep into neural tissue without increasing the stiffness or size of the electrodes will enable minimally invasive electrical recordings from within the brain. Here we show that specially designed microfluidic devices can apply a tension force to ultraflexible electrodes that prevents buckling without increasing the thickness or stiffness of the electrode during implantation. Additionally, these “fluidic microdrives” allow us to precisely actuate the electrode position with micron-scale accuracy. To demonstrate the efficacy of our fluidic microdrives, we used them to actuate highly flexible carbon nanotube fiber (CNTf) microelectrodes for electrophysiology. We used this approach in three proof-of-concept experiments. First, we recorded compound action potentials in a soft model organism, the small cnidarian <i>Hydra</i>. Second, we targeted electrodes precisely to the thalamic reticular nucleus in brain slices and recorded spontaneous and optogenetically evoked extracellular action potentials. Finally, we inserted electrodes more than 4 mm deep into the brain of rats and detected spontaneous individual unit activity in both cortical and subcortical regions. Compared to syringe injection, fluidic microdrives do not penetrate the brain and prevent changes in intracranial pressure by diverting fluid away from the implantation site during insertion and actuation. Overall, the fluidic microdrive technology provides a robust new method to implant and actuate ultraflexible neural electrodes

Measurements of the Total and Differential Higgs Boson Production Cross Sections Combining the H??????? and H???ZZ*???4??? Decay Channels at s\sqrt{s}=8??????TeV with the ATLAS Detector

Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3~fb$^{-1}$ of $pp$ collisions produced by the Large Hadron Collider at a center-of-mass energy of $\sqrt{s} = 8$ TeV and recorded by the ATLAS detector. Cross sections are obtained from measured $H \rightarrow \gamma \gamma$ and $H \rightarrow ZZ ^{*}\rightarrow 4\ell$ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be $\sigma_{pp \to H} = 33.0 \pm 5.3 \, ({\rm stat}) \pm 1.6 \, ({\rm sys}) \mathrm{pb}$. The measurements are compared to state-of-the-art predictions.Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3  fb-1 of pp collisions produced by the Large Hadron Collider at a center-of-mass energy of s=8  TeV and recorded by the ATLAS detector. Cross sections are obtained from measured H→γγ and H→ZZ*→4ℓ event yields, which are combined accounting for detector efficiencies, fiducial acceptances, and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be σpp→H=33.0±5.3 (stat)±1.6 (syst)  pb. The measurements are compared to state-of-the-art predictions.Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3 fb$^{-1}$ of $pp$ collisions produced by the Large Hadron Collider at a center-of-mass energy of $\sqrt{s} = 8$ TeV and recorded by the ATLAS detector. Cross sections are obtained from measured $H \rightarrow \gamma \gamma$ and $H \rightarrow ZZ ^{*}\rightarrow 4\ell$ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be $\sigma_{pp \to H} = 33.0 \pm 5.3 \, ({\rm stat}) \pm 1.6 \, ({\rm sys}) \mathrm{pb}$. The measurements are compared to state-of-the-art predictions