Search NASA⌕ Search

SEARCH · Search NASA

Results for “COMMUNICATIONS NETWORKS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Microkinetic modeling of aqueous phase biomass conversion: Application to ethylene glycol reforming

In this communication, we develop automatically a reaction network for ethylene glycol reforming on Pt. We employ a recently introduced group additivity scheme for estimation of thermochemistry over metal catalysts in vapor phase and in solution along with Brønsted-Evans-Polanyi (BEP) relations for vapor phase kinetics to parameterize microkinetic models for vapor and aqueous phases. Unlike vapor-phase reforming, we show that solvent occupies a significant fraction of surface sites and by doing this, it shifts the water-gas shift reaction to CO2 and H2 and avoids poisoning of the catalyst by CO. The model is found to be in reasonable agreement with the experimental data.

bio-inspired↗
DOE OSTI2019

Estimation of RTT and Loss Rate of Wide-Area Connections Using MPI Measurements

Scientific computations are expected to be increasingly distributed across wide-area networks, and the Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. These computations should account for certain network parameters to ensure an effective execution, for example, by avoiding highly congested and long connections. The execution times of MPI basic operations reflect the connection parameters, including the Round Trip Time (RTT) and loss rate. We describe five machine leaning methods to estimate the connection RTT and loss rate using execution times of MPI basic operations. We utilize execution time measurements of MPI Sendrecv operations collected over emulated 10 Gbps connections with 0-366 ms round-trip times, wherein the longest connection spans the globe, under up to 20% periodic losses. These methods provide disparate, namely, linear and non-linear, and smooth and non-smooth, estimates of RTT and loss rate. Our results show that accurate estimates can be generated at low loss rates but they become inaccurate at loss rates 10% and higher. Overall, these results constitute a case study of the strengths and limitations of machine learning methods in inferring network-level parameters using application-level measurements.

Rao, Nageswara S.↗
DOE OSTI2021

Adaptive Threshold-Based Zonal Isolation of Faults in a Multiterminal DC Using Local Measurements

Fast and accurate methods of fault detection and isolation are a pre-emptive measure in multiterminal dc (MTdc) systems. Zonal isolation of faults is necessary to prevent any misopertation of the dc breakers that can lead to a shutdown of the network. Existing techniques require fast-communication or data synchronization methods have their own disadvantages. This article proposes a method for efficient fault zone isolation without the need of a communication link that prevents any misoperation of the dc breakers in a radial MTdc. This method provides individual local measurement-based control to the hybrid dc circuit breakers (dcCB). Faults created outside the zone of protection for a breaker create a change in the rate of change of current or voltage leading to misoperation. To avoid detection using a fixed threshold, an adaptive threshold based approach is suggested that updates the threshold based on the present operating status. Sensitivity analysis by varying the current limiting inductance and fault location is performed. In conclusion, a three terminal radial model of an MTdc is used for zonal isolation using power system computer aided design/electromagnetic transients including dc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Seamless Wireless Communication Platform for Internet of Things Applications

The rapid growth of the Internet of Things (IoT) devices resulted in the proliferation of wireless technologies to cater to their increasing data rate requirements and support multiple applications. However, such ever-increasing wireless technologies present numerous challenges such as incompatible wireless standards, increased energy consumption, and insecure communication. The traditional gateways proposed in the literature suffers from limitations such as computational complexity, resource requirements, increased cost, and device size. We vision an era of seamless wireless communication to alleviate the aforementioned challenges in IoT applications. through three inter-dependent functionalities namely detection and identification of wireless technologies, energy-efficient transmit power control, and secure end-to-end communication. To prove the concept, a new gateway is proposed to achieve these three functionalities with only physical layer measurements so that the different communication protocols in the higher layers can be avoided. Novel schemes are conceptualized for resource-limited seamless IoT applications. Moreover, the conceptual seamless IoT platform is validated through software-based computer simulation and software-defined radio-based testbed implementation. Finally, the preliminary analysis demonstrates that the proposed platform has great potential in advancing seamless IoT applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Volt/VAR Optimization (VVO) Application on GridAPPS-D Platform

There is a large increment in the distributed energy resources (DERs) installation and deployments of smart sensing devices and communication infrastructure; hence, the power distribution network is swiftly evolving from a passive network to an active network. This motivates the development of advanced applications to operate power distribution systems for higher efficiency and reliability. These advanced applications are model-based and data-driven. This requires an advanced distribution management system (ADMS) to provide required data for the optimal operation of the distribution systems by coordinating various grid controllable devices. In this paper a Volt-VAR optimization (VVO) application to coordinate the grid’s legacy and new voltage control devices for conservation voltage reduction (CVR) is deployed on the GridAPPS-D platform (an open-source platform ) for ADMS application development. The VVO application is validated for various operating conditions on using modified IEEE 8500-node distribution test feeders. Further, the application is successfully deployed on the GridAPPS-D platform.

Jha, Rahul↗
DOE OSTI2014

Avalaunch

Avalaunch implements a tree-based process launcher. It first bootstraps itself on to a set of compute nodes by launching children processes, which immediately connect back to the parent process to acquire info needed t launch their own children. Once the tree is established, user processes are started by broadcasting commands and application binaries through the tree. All communication flows over high-performance network protocols via spawnnet. The goal is to start MPI jobs having hundreds of thousands of processes within seconds.

Moody, A.T.↗
DOE OSTI2024

Globus service enhancements for exascale applications and facilities

Many extreme-scale applications require the movement of large quantities of data to, from, and among leadership computing facilities, as well as other scientific facilities and the home institutions of facility users. These applications, particularly when leadership computing facilities are involved, can touch upon edge cases (e.g., terabyte files) that had not been a focus of previous Globus optimization work, which had emphasized rather the movement of many smaller (megabyte to gigabyte) files. We report here on how automated client-driven chunking can be used to accelerate both the movement of large files and the integrity checking operations that have proven to be essential for large data transfers. In conclusion, we present detailed performance studies that provide insights into the benefits of these modifications in a range of file transfer scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Evaluating System Parameters on a Dragonfly using Simulation and Visualization

The dragon y topology is becoming a popular choice for build- ing high-radix, low-diameter networks with high-bandwidth links. Even with a powerful network, preliminary experi- ments on Edison at NERSC have shown that for communica- tion heavy applications, job interference and thus presumably job placement remains an important factor. In this paper, we explore the e ects of job placement, job sizes, parallel workloads and network con gurations on network through- put to better understand inter-job interference. We use a simulation tool called Damsel y to model the network be- havior of Edison and study the impact of various system parameters on network throughput. Parallel workloads based on ve representative communication patters are used and the simulation studies on up to 131,072 cores are aided by a new visualization of the dragon y network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Economic and Physical Linkages of the Information and Communication Technology (ICT) Service Industry to Key Industries of the Economy: An Ad Hoc Report

This report examines the information and communications technology (ICT) services industry in response to an inquiry by the Department of Energy’s (DOE’s) Office of Energy Policy and Systems Analysis. The report answers several key questions: •How has the reliance on ICT services evolved in recent years for key infrastructure services such as air travel, freight transport, electricity and natural gas distribution, financial services, and critical health care, and for the household sector? •What ICT industry trends explain continued strong linkage to and reliance upon ICT? •What is the ICT industry’s reliance on grid-supplied power, uninterruptible power supplies, emergency generators and back-up energy storage technologies? •What are the observed direct effects of ICT disruptions induced by electrical system failures in recent history and how resilient are the components of the ICT industry?

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Adapting Secure MultiParty Computation to Support Machine Learning in Radio Frequency Sensor Networks

In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

42 ENGINEERING↗
DOE OSTI2023

Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops

Over the past decade, fundamental changes in artificial intelligence (AI)—from foundational to applied—have delivered dramatic insights across a wide breadth of U.S. Department of Energy (DOE) mission space. AI is helping to augment and improve scientific and engineering workflows (e.g., for control, design, and dramatic performance gains through surrogate models) in national security, the Office of Science, and DOE’s applied energy programs. The progress and potential for AI in DOE science was captured in the 2020 “AI for Science” report from the DOE laboratory community in collaboration with academia and industry. Specific scientific areas ready to further leverage the power of AI ranged from the scale and performance of computational models to data analysis to creating new classes of observations using computer vision. Since that report, the scale and scope of scientific AI have accelerated, revealing new, emergent properties that yield insights that go beyond enabling opportunities to being potentially transformative in the way that scientific problems are posed and solved. Thus, under the guidance of both the Office of Science (SC) and the National Nuclear Security Administration (NNSA), the DOE national laboratories organized a series of workshops in 2022 to gather input on new and rapidly emerging opportunities and challenges of scientific AI. This 2023 report is a synthesis of those workshops. The scientific community believes AI can have a foundational impact on a broad range of DOE missions, including science, energy, and national security. Further, DOE has unique capabilities that enable the community to drive progress in scientific use of AI, building on long-standing DOE strengths and investments in computation, data, and communications infrastructure, spanning the Energy Sciences Network (ESnet), the Exascale Computing Project (ECP), and integrative programs such as the NNSA Office of Defense Programs Advanced Simulation and Computing (ASC) and the SC Scientific Discovery through Advanced Computing (SciDAC) programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Resilient Autonomous Wind Farms

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm level, taking into account individual wind turbine information to achieve wind-farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have experienced significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms that can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as from local meteorological stations, nearby radars, sodars, and lidars, and supervisory control and data acquisition (SCADA) data. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and ensuring more efficient overall control of farmwide optimizations through mechanisms such as wake steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach that distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks that seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft-Byzantine-Fault-Tolerant algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will...

fault tolerance↗
DOE OSTI2020

Syncytia in Fungi

Filamentous fungi typically grow as interconnected multinucleate syncytia that can be microscopic to many hectares in size. Mechanistic details and rules that govern the formation and function of these multinucleate syncytia are largely unexplored, including details on syncytial morphology and the regulatory controls of cellular and molecular processes. Recent discoveries have revealed various adaptations that enable fungal syncytia to accomplish coordinated behaviors, including cell growth, nuclear division, secretion, communication, and adaptation of the hyphal network for mixing nuclear and cytoplasmic organelles. In this review, we highlight recent studies using advanced technologies to define rules that govern organizing principles of hyphal and colony differentiation, including various aspects of nuclear and mitochondrial cooperation versus competition. We place these findings into context with previous foundational literature and present still unanswered questions on mechanistic aspects, function, and morphological diversity of fungal syncytia across the fungal kingdom.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters

Bayesian inference is used to calibrate a bottom-up home PLC network model with unknown loads and wires at frequencies up to 30 MHz. A network topology with over 50 parameters is calibrated using global sensitivity analysis and transitional Markov Chain Monte Carlo (TMCMC). The sensitivity-informed Bayesian inference computes Sobol indices for each network parameter and applies TMCMC to calibrate the most sensitive parameters for a given network topology. A greedy random search with TMCMC is used to refine the discrete random variables of the network. This results in a model that can accurately compute the transfer function despite noisy training data and a high dimensional parameter space. The model is able to infer some parameters of the network used to produce the training data, and accurately computes the transfer function under extrapolative scenarios.

42 ENGINEERING↗
DOE OSTI2014

Avalaunch

Avalaunch implements a tree-based process launcher. It first bootstraps itself on to a set of compute nodes by launching children processes, which immediately connect back to the parent process to acquire info needed t launch their own children. Once the tree is established, user processes are started by broadcasting commands and application binaries through the tree. All communication flows over high-performance network protocols via spawnnet. The goal is to start MPI jobs having hundreds of thousands of processes within seconds.

Moody, A. T.↗
DOE OSTI2017

Network resiliency through memory health monitoring and proactive management

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Resilient Autonomous Wind Farms: Preprint

With the advent of an increasing number of control strategies that seek to optimize wind turbine performance on a farm-level, taking account of individual wind turbine information to achieve wind farm-level objectives has become an increasingly important goal. Methods for controlling wind turbines on an individual and farm level have seen significant development, and an abundance of new implementations for gathering and using data from turbines have created potential for novel control mechanisms which can further optimize the performance and delivery characteristics of a wind farm. A key element of making these wind farms more efficient is to develop reliable algorithms that use local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. Making use of information from all wind turbines in a wind farm can enable such approaches as determining the atmospheric conditions across the farm, improving fault-finding, and enabling more efficient overall control of farm-wide optimizations through mechanisms such as wake-steering. However, these approaches typically involve a centralized communications and control center. In order to ensure the resilient operation of the farm, it is necessary to develop an approach which distributes the calculation and communication amongst multiple nodes throughout the farm. In this fashion, a redundant, robust, and secure network can be created, which can tolerate faults in calculation, communication, and even external attacks which seek to disrupt the operation of the wind farm. This paper introduces the use of the Raft Byzantine Fault Tolerance algorithm in the implementation of autonomous control of a wind farm. This implementation will allow for fault tolerance for malfunctioning nodes, sensors, transmitters, and connectors. This approach is equally extensible to account for malicious actors. It will be shown to achieve overall consensus, provided the number of faults/malicious nodes is less than 3$n$+1, where $n$ is the number of turbine cluster faults which may occur, and to be robust in the face of multiple arbitrary faults.

autonomous↗
DOE OSTI2021

Network resiliency through memory health monitoring and proactive management

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

Andrade Costa, Carlos H.↗