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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Optimal Network-Topology Design

Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.

Li, Victor O. K.↗

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.

Distributed sensing↗

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗

Telecommunications network optimization

Analysis discusses STACOM (state criminal justic communication) network topology program used to design and evaluate digital telecommunications networks STACOM employs ESAU-WILLIAMS technique to search for direct links between system terminations and regional switching center. Inputs include traffic data, terminal locations, and functional requirements.

Lee, J.↗

Toward Optimal Transport Networks

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Alexandrov, Natalia↗

A Robust Scalable Transportation System Concept

This report documents the 2005 Revolutionary System Concept for Aeronautics (RSCA) study entitled "A Robust, Scalable Transportation System Concept". The objective of the study was to generate, at a high-level of abstraction, characteristics of a new concept for the National Airspace System, or the new NAS, under which transportation goals such as increased throughput, delay reduction, and improved robustness could be realized. Since such an objective can be overwhelmingly complex if pursued at the lowest levels of detail, instead a System-of-Systems (SoS) approach was adopted to model alternative air transportation architectures at a high level. The SoS approach allows the consideration of not only the technical aspects of the NAS", but also incorporates policy, socio-economic, and alternative transportation system considerations into one architecture. While the representations of the individual systems are basic, the higher level approach allows for ways to optimize the SoS at the network level, determining the best topology (i.e. configuration of nodes and links). The final product (concept) is a set of rules of behavior and network structure that not only satisfies national transportation goals, but represents the high impact rules that accomplish those goals by getting the agents to "do the right thing" naturally. The novel combination of Agent Based Modeling and Network Theory provides the core analysis methodology in the System-of-Systems approach. Our method of approach is non-deterministic which means, fundamentally, it asks and answers different questions than deterministic models. The nondeterministic method is necessary primarily due to our marriage of human systems with technological ones in a partially unknown set of future worlds. Our goal is to understand and simulate how the SoS, human and technological components combined, evolve.

Hahn, Andrew↗

Neural networks for aircraft control

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Linse, Dennis↗

Krylov methods preconditioned with incompletely factored matrices on the CM-2

The performance is measured of the components of the key interative kernel of a preconditioned Krylov space interative linear system solver. In some sense, these numbers can be regarded as best case timings for these kernels. Sweeps were timed over meshes, sparse triangular solves, and inner products on a large 3-D model problem over a cube shaped domain discretized with a seven point template. The performance of the CM-2 is highly dependent on the use of very specialized programs. These programs mapped a regular problem domain onto the processor topology in a careful manner and used the optimized local NEWS communications network. The rather dramatic deterioration in performance was documented when these ideal conditions no longer apply. A synthetic workload generator was developed to produce and solve a parameterized family of increasingly irregular problems.

Berryman, Harry↗

Computer-oriented synthesis of wide-band non-uniform negative resistance amplifiers

This paper presents a synthesis procedure which provides design values for broad-band amplifiers using non-uniform negative resistance devices. Employing a weighted least squares optimization scheme, the technique, based on an extension of procedures for uniform negative resistance devices, is capable of providing designs for a variety of matching network topologies. It also provides, for the first time, quantitative results for predicting the effects of parameter element variations on overall amplifier performance. The technique is also unique in that it employs exact partial derivatives for optimization and sensitivity computation. In comparison with conventional procedures, significantly improved broad-band designs are shown to result.

Branner, G. R.↗

The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic

We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.

Armstrong, Curtis D.↗

Optimal Sensor Mobility Design for Target Tracking with Distributed Sensing, Communication and Computing Infrastructure

The paper presents an airborne target tracking approach with data fusion from distributed stationary and mobile sensor network transmitted through a wireless/wired communication network and using a distributed computing infrastructure. To obtain high quality measurements, sensor flight platforms' positions and orientations are optimized with respect to the available target's position and velocity estimates, and a formation control strategy is applied to derive desired trajectories for the flight platforms. As sensors move, the communication network topology switching is determined using the worst-case approach to handle uncertainties in the target's and sensors' positions, which alters communication delays for sensors' data transmission to computing centers. An optimal data migration algorithm is periodically applied to determine these communication delays for each sensor and the optimal location with minimum end-to-end latency for the target tracking algorithm execution, which is based on adaptive information fusion from multi-modal mobile and stationary sensors inside an Extended Kalman Filter framework. The approach is validated in a desktop simulation environment using synthetic sensor data generated for a simulated target's flight.

Distributed sensing↗

Applying the Cognitive Space Gateway to Swarm Topologies

NASA's future vision for interplanetary networking includes a lunar network, Cube Satellite (CubeSat) constellations, and deep space robotic missions, comprising what could be viewed as a network of networks. Delay-tolerant networking (DTN) architecture and protocols provide a standard network layer among these varying scenarios and mitigate many challenges of the space environment, such as long delays, unplanned service interruptions, and asymmetric links. The Cognitive Space Gateway (CSG) is a routing method in a DTN architecture that uses spiking neural networks as the learning element to optimize routing decisions in a complex environment. This work aims to further develop cognitive networking technologies in several critical areas, including DTN, the CSG algorithm, CubeSat swarm topologies, and cloud services. To test the algorithm in a realistic scenario, the emulated network topology is based on a CubeSat swarm. The swarm may function as a mesh of nodes or as a hub-and-spoke network. An emulation environment will be built upon a commercial cloud service, such as Amazon Web Services (AWS) Elastic Compute Cloud. The cloud environment may enable a flexible, lower maintenance approach versus a multi-hop network based in a physical laboratory. The cloud platform will provide a secure environment allowing for collaboration among government and academic entities.

Ricardo Lent↗

Applying the Cognitive Space Gateway to Swarm Topologies

NASA’s future vision for interplanetary networking includes a lunar network, Cube Satellite (CubeSat) constellations, and deep space robotic missions, comprising what could be viewed as a network of networks. Delay-tolerant networking (DTN) architecture and protocols provide a standard network layer among these varying scenarios and mitigate many challenges of the space environment, such as long delays, unplanned service interruptions, and asymmetric links. The Cognitive Space Gateway (CSG) is a routing method in a DTN architecture that uses spiking neural networks as the learning element to optimize outing decisions in a complex environment. This work aims to further develop cognitive networking technologies in several critical areas, including DTN, the CSG algorithm, SmallSat swarm topologies, and cloud services. The CSG algorithm is tested in a realistic scenario in which the emulated network topology is based on a SmallSat swarm. The emulation environment will be built upon a commercial cloud service, such as Amazon Web Services (AWS) Elastic Compute Cloud. This work investigates the ability of such a platform to enable a flexible, lower maintenance approach to creating a multihop network outside of a physical laboratory. The cloud platform will provide a secure environment allowing for collaboration among government and academic entities.

Ricardo Lent↗

Large-Scale Space Network Simulator for Performance-Optimized DTNs

High-rate Delay Tolerant Networking (HDTN) is a performance-optimized Delay Tolerant Networking (DTN) implementation that can provide multigigabit per second data rates in disruptive and high-latency space networks. Routing, especially in large-scale space networks, remains challenging due to network topologies that evolve over time. This paper presents a simulation tool that enables HDTN implementation testing at accelerated speeds, which is key for routing in large-scale space networks.

High data-rate Delay Tolerant Networking↗

Communication Needs Assessment for Distributed Turbine Engine Control

Control system architecture is a major contributor to future propulsion engine performance enhancement and life cycle cost reduction. The control system architecture can be a means to effect net weight reduction in future engine systems, provide a streamlined approach to system design and implementation, and enable new opportunities for performance optimization and increased awareness about system health. The transition from a centralized, point-to-point analog control topology to a modular, networked, distributed system is paramount to extracting these system improvements. However, distributed engine control systems are only possible through the successful design and implementation of a suitable communication system. In a networked system, understanding the data flow between control elements is a fundamental requirement for specifying the communication architecture which, itself, is dependent on the functional capability of electronics in the engine environment. This paper presents an assessment of the communication needs for distributed control using strawman designs and relates how system design decisions relate to overall goals as we progress from the baseline centralized architecture, through partially distributed and fully distributed control systems.

Culley, Dennis E.↗

Some Aeronautical Communications Experiments

Classically there has existed an asymmetry between the computing and communicating sides of aerospace systems. Over the past few decades, this asymmetry has shifted to favoring communication link technologies, meaning that advancements in available central processing units (CPUs), storage devices, and internal data buses have stagnated. Indeed, the increased emphasis placed on refining subsystem performance such as with antenna bandwidth in phased arrays, amplifier power efficiency, software defined radio (SDR) flexibility and encoding for data compression and error correction has given rise to successful debuts of multi-gigabit-per-second data return from long space-link distances. These accomplishments are easily quantifiable through link budgets and illustrate what is possible, but also reveal the deficiencies in overall communications capabilities. In particular, the ever-accelerating presence of aerospace vehicles gives rise to newer and larger classes of challenges to address the needs of 21st century systems. Furthermore remote sensing and imaging capabilities have far outpaced our ability to transmit their products to the ground, so we are increasingly dependent on pre-processing and downselection to contend with the communications bottleneck. No longer may we depend upon the constrained logistics in delivering end-to-end data delivery through manual reconfigurations, static event scheduling and execution on a per-vehicle basis, for these methods do not scale and therefore must give way to dynamic, networked approaches with an overall systems view in mind. Emerging mission requirements exhibit a trend toward multiple smaller-scale vehicles working together to perform dissimilar observations. Such operations necessitate sensor fusion across a constellation, and where data processing may be distributed throughout a fairly disconnected network whose topology changes over time in non-deterministic manners. Individual communications link performance is still very relevant to deploying an effective communications system, but now must be embedded within a greater architecture of capability to optimally utilize the bandwidth available from each link to generate an ultimate end-to-end quality of service. The deleterious effects of timing uncertainty across the arrangement presents a challenge to measurement synchronization and delivery, so a successful deployed system needs to be tolerant to the delays inherent in time-of-light between elements and digital processing latencies existing at each node. In this presentation we share the flight test results from a high performance Gbps laser communications terminal evaluated with a suite of store and forward capabilities called High-rate Delay Tolerant Networking (HDTN). The communications payload is operated over Lake Erie across a range of configurations including several convergence layers, and is evaluated to determine recovery time after link disruptions, information loss, efficiency and speed. The effectiveness of utilizing a flying laboratory to increase the Technology Readiness Level (TRL) of an integrated system in relevant environments is discussed, as well as the value of conducting aeronautics experiments to retire risk for technology infusion into space missions. Upcoming flight campaigns will be presented, including opportunities to demonstrate secure command and control, data intensive hyperspectral imaging, quantum link characterization, 4k High Definition (HD) video streaming and internetworked space-ground-aero relay operations. These experiments will pave the way for future missions which will depend upon interoperability across disparate government and privately owned networks, involve contention with uncertain and dynamic timing, and require agility to autonomously configure optimal parameters across networks of ever-increasing size and complexity to ensure data delivery. https://www1.grc.nasa.gov/space/scan/acs/tech-studies/dtn/

Daniel Raible↗

4K High Definition Video and Audio Streaming Across High-rate Delay Tolerant Space Networks

Audio and video streaming across delay tolerant networks are relatively new phenomena. During the Apollo 11 mission, video and audio were streamed directly back to Earth using fully analog radios. This streaming capability atrophied over time due to the gradual conversion to digital electronics accompanied with higher resolutions causing the required bit rates to outpace communication link performance. Additionally, 21st century space systems face the new requirement of interconnectedness. Delay Tolerant Networking (DTN) attempts to solve this requirement by uniting traditional point to point links into a robust and dynamic network. However, In order to avoid system bottlenecks, the High-Rate Delay Tolerant Networking (HDTN) implementation focuses on performance-optimization of the standards. This work extends the functionality of HDTN by implementing audio and video streaming, with the goal of demonstrating the practical application of high definition media streaming across space networks. A series of network topologies were created including simple point to point links and multi-node multi-hop networks. Test media in the form of prerecorded and live footage was streamed across the network. A set of objective quality metrics were established in order to measure the stream quality. A lunar network was emulated using a mixture of embedded ARM platforms.

Kyle J Vernyi↗

TPSAS-NF1676L-12321-DND

The operation of some networks, such as air transportation networks, can be complicated by congestion through a small subset of nodes. The congestion may be influenced by the connectivity of the network, or by the presence of constraints restricting the flow through particular nodes. This work investigates the effects of both connectivity and node flow constraints on the operation of a network. We develop the Minimax Node Load Problem (MNLP), a multicommodity flow model which minimizes the worst-case flow through any node in a given input network. The optimal solution to this problem provides us with the minimax node load, which we propose as a measure of network congestion. Keeping the number of nodes fixed, we first increase connectivity in a series of networks, and observe that topologies with more distributed connections result in a reduction in the minimax node load. However, when connectivity is increased further, the reductions diminish and are accompanied by solutions with undesirable qualities such as longer commodity paths. We then perform a second set of experiments over the same network, constraining flow through different subsets of nodes at different magnitudes of flow restriction, finding that (1) more constrained nodes lead to the largest increases in minimax node load and (2) constraints on the most connected nodes have the greatest effect on both congestion and commodity path length.

Douglas W Lee↗