Use of Virtual Network Simulator in Satellite and Terrestrial Interoperability Testbed
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Virtual Network Simulator Testbed hardware network↗
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Network Emulation Testbed Capabilities for Prototyping Space DTN Software and Protocols
This paper delves into network emulation tools essential for evaluating and designing Delay Tolerant Networking (DTN) protocols in space and satellite networking. It surveys and assesses the capability of current testbeds to create realistic test environments crucial for developing and evaluating DTN protocols. Specifically, this study provides a comprehensive overview of key DTN protocol stacks and related network emulation platforms and a detailed exploration of NASA’s research facilities. Finally, the paper underscores the fundamental emulation capabilities and the importance of a standardized framework for scenario creation, highlighting its vital role in evaluating and advancing future emulation platforms for space DTN.
Network Emulation and Simulation↗
The TAVERNS emulator: An Ada simulation of the space station data communications network and software development environment
The Space Station DMS (Data Management System) is the onboard component of the Space Station Information System (SSIS) that includes the computers, networks and software that support the various core and payload subsystems of the Space Station. TAVERNS (Test And Validation Environment for Remote Networked Systems) is a distributed approach for development and validation of application software for Space Station. The TAVERNS concept assumes that the different subsystems will be developed by different contractors who may be geographically separated. The TAVERNS Emulator is an Ada simulation of a TAVERNS on the ASD VAX. The software services described in the DMS Test Bed User's Manual are being emulated on the VAX together with simulations of some of the core subsystems and a simulation of the DCN. The TAVERNS Emulator will be accessible remotely from any VAX that can communicate with the ASD VAX.
Howes, Norman R.↗
Interfacing Space Communications and Navigation Network Simulation with Distributed System Integration Laboratories (DSIL)
NASA's planned Lunar missions will involve multiple NASA centers where each participating center has a specific role and specialization. In this vision, the Constellation program (CxP)'s Distributed System Integration Laboratories (DSIL) architecture consist of multiple System Integration Labs (SILs), with simulators, emulators, testlabs and control centers interacting with each other over a broadband network to perform test and verification for mission scenarios. To support the end-to-end simulation and emulation effort of NASA' exploration initiatives, different NASA centers are interconnected to participate in distributed simulations. Currently, DSIL has interconnections among the following NASA centers: Johnson Space Center (JSC), Kennedy Space Center (KSC), Marshall Space Flight Center (MSFC) and Jet Propulsion Laboratory (JPL). Through interconnections and interactions among different NASA centers, critical resources and data can be shared, while independent simulations can be performed simultaneously at different NASA locations, to effectively utilize the simulation and emulation capabilities at each center. Furthermore, the development of DSIL can maximally leverage the existing project simulation and testing plans. In this work, we describe the specific role and development activities at JPL for Space Communications and Navigation Network (SCaN) simulator using the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to simulate communications effects among mission assets. Using MACHETE, different space network configurations among spacecrafts and ground systems of various parameter sets can be simulated. Data that is necessary for tracking, navigation, and guidance of spacecrafts such as Crew Exploration Vehicle (CEV), Crew Launch Vehicle (CLV), and Lunar Relay Satellite (LRS) and orbit calculation data are disseminated to different NASA centers and updated periodically using the High Level Architecture (HLA). In addition, the performance of DSIL under different traffic loads with different mix of data and priorities are evaluated.
Traffic Measuring and Monitoring↗
System analysis for the Huntsville Operation Support Center distributed computer system
A simulation model of the NASA Huntsville Operational Support Center (HOSC) was developed. This simulation model emulates the HYPERchannel Local Area Network (LAN) that ties together the various computers of HOSC. The HOSC system is a large installation of mainframe computers such as the Perkin Elmer 3200 series and the Dec VAX series. A series of six simulation exercises of the HOSC model is described using data sets provided by NASA. The analytical analysis of the ETHERNET LAN and the video terminals (VTs) distribution system are presented. An interface analysis of the smart terminal network model which allows the data flow requirements due to VTs on the ETHERNET LAN to be estimated, is presented.
Ingels, F. M.↗
FPGA Based Reconfigurable ATM Switch Test Bed
Various issues associated with "FPGA Based Reconfigurable ATM Switch Test Bed" are presented in viewgraph form. Specific topics include: 1) Network performance evaluation; 2) traditional approaches; 3) software simulation; 4) hardware emulation; 5) test bed highlights; 6) design environment; 7) test bed architecture; 8) abstract sheared-memory switch; 9) detailed switch diagram; 10) traffic generator; 11) data collection circuit and user interface; 12) initial results; and 13) the following conclusions: Advances in FPGA make hardware emulation feasible for performance evaluation, hardware emulation can provide several orders of magnitude speed-up over software simulation; due to the complexity of hardware synthesis process, development in emulation is much more difficult than simulation and requires knowledge in both networks and digital design.
Chu, Pong P.↗
Towards a High Fidelity Training Environment for Autonomous Cyber Defense Agents
Cyber defenders are overwhelmed by the frequency and scale of attacks against their networks. This problem will only be exacerbated as attackers leverage AI to automate their workflows. Autonomous cyber defense capabilities could aid defenders by automating operations and adapting dynamically to novel threats. However, existing training environments fall short in areas such as generalization, explainability, scalability, and transferability, making it intractable to train agents that will be effective in real networks. In this paper we take an important step towards creating autonomous cyber defense agents — we present a high fidelity training environment called Cyberwheel that includes both simulation and emulation capabilities. Cyberwheel simplifies customization of the training network and easily allows redefining the agent’s reward function, observation space, and action space to support rapid experimentation of novel approaches to agent design. It also provides visibility into agent behaviors necessary for agent evaluation and sufficient documentation / examples to lower the barrier to entry. As an example use case of Cyberwheel, we present initial results training an autonomous agent to deploy cyber deception strategies in simulation.
Oesch, T↗
Neural network based emulation of galaxy power spectrum covariances: A reanalysis of BOSS DR12 data
We train neural networks to quickly generate redshift-space galaxy power spectrum covariances from a given parameter set (cosmology and galaxy bias). This covariance emulator utilizes a combination of traditional fully connected network layers and transformer architecture to accurately predict covariance matrices for the high redshift, north galactic cap sample of the BOSS DR12 galaxy catalog. We run simulated likelihood analyses with emulated and brute-force computed covariances, and we quantify the network’s performance via two different metrics: (1) difference in Χ 2 and (2) likelihood contours for simulated BOSS DR 12 analyses. We find that the emulator returns excellent results over a large parameter range. We then use our emulator to perform a reanalysis of the BOSS HighZ NGC galaxy power spectrum, and find that varying covariance with cosmology along with the model vector produces Ω m = $0.276$$^{+0.013}_{–0.015}$, H 0 = 70.2 ± 1.9 km/s/Mpc, and σ 8 = $0.674$$^{+0.058}_{–0.077}$. These constraints represent an average 0.46σ shift in best-fit values and a 5% increase in constraining power compared to fixing the covariance matrix (Ω m = 0.293 ± 0.017, H 0 = 70.3 ± 2.0 km/s/Mpc, σ 8 = $0.702$$^{+0.063}_{–0.075}$). As a result, this work demonstrates that emulators for more complex cosmological quantities than second-order statistics can be trained over a wide parameter range at sufficiently high accuracy to be implemented in realistic likelihood analyses.
79 ASTRONOMY AND ASTROPHYSICS↗
Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations
We introduce the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) project, an innovative approach to understanding the astrophysical implications of alternative dark matter (DM) models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over DM physics, astrophysics, and cosmology in modeling a range of systems—from galaxy clusters to ultra-faint satellites. Such extensive simulation suites can provide adequate training sets for machine-learning-based analyses. This paper introduces two new cosmological hydrodynamical suites of warm dark matter (WDM), each comprising 1024 simulations generated using the arepo code. One suite consists of uniform-box simulations covering a ${(25\,{h}^{-1}\,{\rm{Mpc}})}^{3}$ volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the WDM particle mass is varied along with the initial density field and several parameters controlling the strength of baryonic feedback within the IllustrisTNG model. We provide two examples, separately utilizing emulators and convolutional neural networks, to demonstrate how such simulation suites can be used to disentangle the effects of DM and baryonic physics on galactic properties. The DREAMS project can be extended further to include different DM models, galaxy formation physics, and astrophysical targets. In this way, it will provide an unparalleled opportunity to characterize uncertainties on predictions for small-scale observables, leading to robust predictions for testing the particle physics nature of DM on these scales.
cosmological parameters↗
Technology Developments Integrating a Space Network Communications Testbed
As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enable its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions. It can simulate entire networks and can interface with external (testbed) systems. The key technology developments enabling the integration of MACHETE into a distributed testbed are the Monitor and Control module and the QualNet IP Network Emulator module. Specifically, the Monitor and Control module establishes a standard interface mechanism to centralize the management of each testbed component. The QualNet IP Network Emulator module allows externally generated network traffic to be passed through MACHETE to experience simulated network behaviors such as propagation delay, data loss, orbital effects and other communications characteristics, including entire network behaviors. We report a successful integration of MACHETE with a space communication testbed modeling a lunar exploration scenario. This document is the viewgraph slides of the presentation.
hybrid simulation↗
Development of Network-based Communications Architectures for Future NASA Missions
Since the Vision for Space Exploration (VSE) announcement, NASA has been developing a communications infrastructure that combines existing terrestrial techniques with newer concepts and capabilities. The overall goal is to develop a flexible, modular, and extensible architecture that leverages and enhances terrestrial networking technologies that can either be directly applied or modified for the space regime. In addition, where existing technologies leaves gaps, new technologies must be developed. An example includes dynamic routing that accounts for constrained power and bandwidth environments. Using these enhanced technologies, NASA can develop nodes that provide characteristics, such as routing, store and forward, and access-on-demand capabilities. But with the development of the new infrastructure, challenges and obstacles will arise. The current communications infrastructure has been developed on a mission-by-mission basis rather than an end-to-end approach; this has led to a greater ground infrastructure, but has not encouraged communications between space-based assets. This alone provides one of the key challenges that NASA must encounter. With the development of the new Crew Exploration Vehicle (CEV), NASA has the opportunity to provide an integration path for the new vehicles and provide standards for their development. Some of the newer capabilities these vehicles could include are routing, security, and Software Defined Radios (SDRs). To meet these needs, the NASA/Glenn Research Center s (GRC) Network Emulation Laboratory (NEL) has been using both simulation and emulation to study and evaluate these architectures. These techniques provide options to NASA that directly impact architecture development. This paper identifies components of the infrastructure that play a pivotal role in the new NASA architecture, develops a scheme using simulation and emulation for testing these architectures and demonstrates how NASA can strengthen the new infrastructure by implementing these concepts.
Slywczak, Richard A.↗
Hardware and Software Integration to Support Real-Time Space Link Emulation
Prior to operational use, communications hardware and software must be thoroughly tested and verified. In space-link communications, field testing equipment can be prohibitively expensive and cannot test to non-ideal situations. In this paper, we show how software and hardware emulation tools can be used to accurately model the characteristics of a satellite communication channel in a lab environment. We describe some of the challenges associated with developing an emulation lab and present results to demonstrate the channel modeling. We then show how network emulation software can be used to extend a hardware emulation model without requiring additional network and channel simulation hardware.
Murawski, Robert↗
Hardware and Software Integration to Support Real-Time Space-Link Emulation
Prior to operational use, communications hardware and software must be thoroughly tested and verified. In space-link communications, field testing equipment can be prohibitively expensive and cannot test to non-ideal situations. In this paper, we show how software and hardware emulation tools can be used to accurately model the characteristics of a satellite communication channel in a lab environment. We describe some of the challenges associated with developing an emulation lab and present results to demonstrate the channel modeling. We then show how network emulation software can be used to extend a hardware emulation model without requiring additional network and channel simulation hardware.
Murawski, Robert↗
Scan2Sim: Software to Convert Network Scans to Emulations
Within operational technology (OT) systems design, the construction of testing environments for simulation is often a tedious, manual process that slows down safety and security evaluations. This document details the design and functionality of Scan2Sim, a program designed to construct high-fidelity topological schematics for OT systems without significant manual human input. Scan2Sim may take as input a detailed network scan of a system, and produces an instruction set to re-create the original scanned network within a virtualized simulation network. This construction is achieved via heuristic methods of machine template selection, which allows for a fast, performant approach to automated environment construction. The current tool is designed to produce topology schematics compatible with the Minimega, a tool designed by Sandia National Laboratories for repeatable experimentation management.
97 MATHEMATICS AND COMPUTING↗
Code for Experiment in Publication “Determining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks”
We plan to release the code used to perform the experiment described in our recent publication, entitled “Determining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks.” This code fits a joint emulator to data from several Discrete Fracture Network (DFN) simulations, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.
Murph, Alexander↗
Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity
Abstract Can the current successes of global machine learning‐based weather simulators be generalized beyond 2‐week forecasts to stable and accurate multiyear runs? The recently developed AI2 Climate Emulator (ACE) suggests this is feasible, based upon 10‐year simulations with a network trained on output from a physics‐based global atmosphere model using a grid spacing of approximately 110 km and forced by a repeating annual cycle of sea‐surface temperature. Here we show that ACE, without modification, can be trained to emulate another major atmospheric model, EAMv2, run at a comparable grid spacing for at least 10 years with similarly small climate biases—a prerequisite to wider applicability. With an analysis that combines multiple temporal, spatial, and frequency domain perspectives, we show that ACE faithfully represents the spatiotemporal structure of EAMv2 precipitation and related variables. Finally, we show that a pretrained ACE network is able to adapt to a new global climate model simulation data set with 10 fewer training steps than when starting from random initialization, all while still maintaining low levels of climate bias. Further analysis of these fine‐tuning experiments reveal ACE's intriguing ability to interpolate between distinct global climate models.
Duncan, James P. C.↗
Uncertainty Quantification for Neutron Shield Using Convolutional Neural Networks
Uncertainty quantification from radiation transport calculations was conducted using a Bayesian inference approach. A surrogate model, using a convolutional neural network, was employed to emulate the neutron fluence, which was simulated with a Monte Carlo radiation transport model. This allowed for a computationally cheap approach to evaluate input parameters and to sample their corresponding posterior probability distributions. Experimental data from the literature were employed to perform uncertainty quantification studies for concrete shields. As a result, the method is a nonintrusive approach that enables studies with multiple input parameters and can be applied to any radiation transport model.
Bayesian inference↗
Satellite ground-terminal user simulation
Realistic simulation of satellite communication systems and evaluation of satellite networking schemes require emulation of the systems's users. A laboratory model of a Ka-band satellite-switched time-division multiple-access (SS-TDMA) communication network, referred to as the System Integration, Test, and Evaluation (SITE) project, uses special bit-error-rate (BER) test sets to simulate the transmitting and receiving users of a communication network. The bit-error-rate test sets contain circuit boards that can be modified to create a variety of interfaces to satellite system ground terminals.
Shalkhauser, Mary Jo W.↗