Results for “networking” — Page 37

NASA NTRS1988

Networking and AI systems: Requirements and benefits

The price performance benefits of network systems is well documented. The ability to share expensive resources sold timesharing for mainframes, department clusters of minicomputers, and now local area networks of workstations and servers. In the process, other fundamental system requirements emerged. These have now been generalized with open system requirements for hardware, software, applications and tools. The ability to interconnect a variety of vendor products has led to a specification of interfaces that allow new techniques to extend existing systems for new and exciting applications. As an example of the message passing system, local area networks provide a testbed for many of the issues addressed by future concurrent architectures: synchronization, load balancing, fault tolerance and scalability. Gold Hill has been working with a number of vendors on distributed architectures that range from a network of workstations to a hypercube of microprocessors with distributed memory. Results from early applications are promising both for performance and scalability.

Source record↗

NASA NTRS1987

VSAT networks - An overview

This paper examines the technology and constraints of very small aperture terminals (VSAT) networks, a special type of wide-area thin-route satellite network that represents a recent innovation in the field of satellite communications. VSAT network architectures suitable for both data and voice communications are studied in this paper. Several issues concerning the frequency of operations, that is, C-band versus Ku-band are examined, and trade-offs between nonspread spectrum and spread spectrum techniques, as well as modulation and multiple access schemes, are considered in detail. Link design examples are given to illustrate the performance of various types of VSAT networks.

Maggenti, Mark↗

NASA NTRS1987

Throughput and packet delay analysis for the H-network - CSMA/CD with adaptive and nonadaptive backoff protocols

The structure of a high-data-rate (about 7 Mbytes/sec) local area network named the H-Network is described which is used to provide point to point analysis and broadcast communication in a multiprocessor environment, the Homogeneous Multiprocessor (Dimopoulos, 1983). The throughput and packet delay characteristics for the H-Network operating under CSMA/CD are presented, using adaptive and nonadaptive backoff protocols. The network is found to perform quite well, with an average utilization factor of over 60 percent and a maximum packet delay of less than 500 microsec for the case of 10 competing stations.

Dimopoulos, Nikitas J.↗

NASA NTRS1987

A unified lunar control network - The near side

A unified lunar control network for the moon's near side, which combines all the data collected by the Lunokhod 2 and Apollo 11, 14, 15, 16, and 17 missions, is presented. Transformations involving translation, rotation, and scale were determined that adjusted the coordinates of the points of three Apollo control networks, computed previously, to the center of mass origin and the mean earth/polar axis coordinate system defined by the lunar ranging retroreflector experiment. The transformed control network computed by the Defense Mapping Agency Aerospace Center was found to be the best fit to the Apollo ALSEP antenna coordinates and was selected as a base to transform all points in Meyer's (1979) telescopic network to the new origin and coordinate system. New coordinates of 1156 of these points are given as are 10 points from a Mariner 10 solution in the north polar region.

Davies, Merton E.↗

NASA NTRS1989

Parallel plan execution with self-processing networks

A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities is being explored. Goals are to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, a model of the execution of a Spaceworld plan was implemented. This is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. It is shown that plan execution, a task usually solved using traditional artificial intelligence (AI) techniques, can be accomplished using a self-processing network. The fact that self-processing networks were applied to other space-related tasks, in addition to the one discussed here, demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. It is also demonstrated that MIRRORS/II is a powerful environment for the development and evaluation of self-processing systems.

Dautrechy, C. Lynne↗

NASA NTRS1988

Development of a space-systems network testbed

This paper describes a communications network testbed which has been designed to allow the development of architectures and algorithms that meet the functional requirements of future NASA communication systems. The central hardware components of the Network Testbed are programmable circuit switching communication nodes which can be adapted by software or firmware changes to customize the testbed to particular architectures and algorithms. Fault detection, isolation, and reconfiguration has been implemented in the Network with a hybrid approach which utilizes features of both centralized and distributed techniques to provide efficient handling of faults within the Network.

Lala, Jaynarayan↗

NASA NTRS1990

Carrying Synchronous Voice Data On Asynchronous Networks

Buffers restore synchronism for internal use and permit asynchronism in external transmission. Proposed asynchronous local-area digital communication network (LAN) carries synchronous voice, data, or video signals, or non-real-time asynchronous data signals. Network uses double buffering scheme that reestablishes phase and frequency references at each node in network. Concept demonstrated in token-ring network operating at 80 Mb/s, pending development of equipment operating at planned data rate of 200 Mb/s. Technique generic and used with any LAN as long as protocol offers deterministic (or bonded) access delays and sufficient capacity.

Bergman, Larry A.↗

NASA NTRS1990

Neural Network Development Tool (NETS)

Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

Baffes, Paul T.↗

NASA NTRS1989

Satellite-matrix-switched, time-division-multiple-access network simulator

A versatile experimental Ka-band network simulator has been implemented at the NASA Lewis Research Center to demonstrate and evaluate a satellite-matrix-switched, time-division-multiple-access (SMS-TDMA) network and to evaluate future digital ground terminals and radiofrequency (RF) components. The simulator was implemented by using proof-of-concept RF components developed under NASA contracts and digital ground terminal and link simulation hardware developed at Lewis. This simulator provides many unique capabilities such as satellite range delay and variation simulation and rain fade simulation. All network parameters (e.g., signal-to-noise ratio, satellite range variation rate, burst density, and rain fade) are controlled and monitored by a central computer. The simulator is presently configured as a three-ground-terminal SMS-TDMA network.

Ivancic, William D.↗

NASA NTRS1990

Distributed simulation of network protocols

Simulations of high speed network protocols are very CPU intensive operations requiring very long run times. Very high speed network protocols (Gigabit/sec rates) require longer simulation runs in order to reach a steady state, while at the same time requiring additional CPU processing for each unit of time because of the data rates for the traffic being simulated. As protocol development proceeds and simulations provide insights into any problems associated with the protocol, the simulation model often must be changed to generate additional or finer statistical performance information. Iterating on this process is very time consuming due to the required run times for the simulation models. The results of the efforts to distribute a high speed ring network protocol, Carrier Sensed Multiple Access/Ring Network (CSMA/RN), are presented.

Paterra, Frank↗

NASA NTRS1989

Computational chaos in massively parallel neural networks

A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

Barhen, Jacob↗

NASA NTRS1990

Behavioral networks as a model for intelligent agents

On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.

Sliwa, Nancy E.↗

NASA NTRS1989

A neural network for controlling the configuration of frame structure with elastic members

A neural network for controlling the configuration of frame structure with elastic members is proposed. In the present network, the structure is modeled not by using the relative angles of the members but by using the distances between the joint locations alone. The relationship between the environment and the joints is also defined by their mutual distances. The analog neural network attains the reaching motion of the manipulator as a minimization problem of the energy constructed by the distances between the joints, the target, and the obstacles. The network can generate not only the final but also the transient configurations and the trajectory. This framework with flexibility and parallelism is very suitable for controlling the Space Telerobotic systems with many degrees of freedom.

Tsutsumi, Kazuyoshi↗

NASA NTRS1989

Parallel plan execution with self-processing networks

A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities is being explored. Goals are to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, a model of the execution of a Spaceworld plan was implemented. This is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. It is shown that plan execution, a task usually solved using traditional artificial intelligence (AI) techniques, can be accomplished using a self-processing network. The fact that self-processing networks were applied to other space-related tasks, in addition to the one discussed here, demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. It is also demonstrated that MIRRORS/II is a powerful environment for the development and evaluation of self-processing systems.

D'Autrechy, C. Lynne↗

NASA NTRS1990

Satellite-matrix-switched, time-division-multiple-access network simulator

A versatile experimental Ka-band network simulator has been implemented at the NASA Lewis Research Center to demonstrate and evaluate a satellite-matrix-switched, time-division-multiple-access (SMS-TDMA) network and to evaluate future digital ground terminals and radiofrequency (RF) components. The simulator was implemented by using proof-of-concept RF components developed under NASA contracts and digital ground terminal and link simulation hardware developed at Lewis. This simulator provides many unique capabilities such as satellite range delay and variation simulation and rain fade simulation. All network parameters (e.g., signal-to-noise ratio, satellite range variation rate, burst density, and rain fade) are controlled and monitored by a central computer. The simulator is presently configured as a three-ground-terminal SMS-TDMA network.

Ivancic, William D.↗

NASA NTRS1988

Hierarchical neural networks for autonomous data analysis and decision making

A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

Eberlein, Susan↗

NASA NTRS1990

The effect of tracking network configuration on GPS baseline estimates for the CASA Uno experiment

The effect of the tracking network on long (greater than 100 km) GPS baseline estimates was estimated using various subsets of the global tracking network initiated by the first Central and South America (CASA Uno) experiment. It was found that best results could be obtained with a global tacking network consisting of three U.S. stations, two sites in the southwestern Pacific, and two sites in Europe. In comparison with smaller subsets, this global network improved the baseline repeatability, the resolution of carrier phase cycle ambiguities, and formal errors of the orbit estimates.

Wolf, S. Kornreich↗

NASA NTRS1990

Sensitivity of feedforward neural networks to weight errors

An analysis is made of the sensitivity of feedforward layered networks of Adaline elements (threshold logic units) to weight errors. An approximation is derived which expresses the probability of error for an output neuron of a large network (a network with many neurons per layer) as a function of the percentage change in the weights. As would be expected, the probability of error increases with the number of layers in the network and with the percentage change in the weights. The probability of error is essentially independent of the number of weights per neuron and of the number of neurons per layer, as long as these numbers are large (on the order of 100 or more).

Stevenson, Maryhelen↗