Electrical network analysis of socio-economic systems utilizing graph theory
Computer program for analyzing New Hampshire highway traffic flow by using models
Lynch, D. D.↗
SEARCH · Engineering Papers
Results for “Network traffic analysis”
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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Calibers: A Bandwidth Calendaring Paradigm for Science Workflows
Many scientific workflows require large data transfers between distributed instrument facilities, storage and computing resources. To ensure that these resources are maximally utilized, R&E networks connecting these resources must ensure that an inherently unpredictable network behaves predictably. In practice, this amounts to the per-application over-provisioning of network resources in an attempt to guarantee that adequate throughput is provided to users. This often results in resource under-utilization over time. One promising solution is the use of deadlines and bandwidth calendaring. In this approach, "fair" resource allocation is replaced with deadline-based resource allocation. However, these approaches often suffer from issues in efficiently regulating resource allocation and failure modes. Therefore, our solution, Calibers, approaches bandwidth calendaring and deadline-awareness in a different way. Calibers uses shaping, metering, and pacing at the edge of the network and end-system to provide participating clients the ability to schedule bandwidth reservations without having to worry about network noise from non-participating clients. Calibers can also fail back to the fair resource allocation of underlying transport protocols if necessary. For example, if a non-participating flow somehow enters the core of the network, or a sudden network change causes the available bandwidth to be exceeded, the underlying transport protocol congestion avoidance implementation will be able to handle the congestion as it normally would. Furthermore, Calibers provides a novel simulation method and resource allocation algorithm.
97 MATHEMATICS AND COMPUTING↗
Delay Tolerant Network Routing as a Machine Learning Classification Problem
This paper discusses a machine learning-based approach to routing for delay tolerant networks (DTNs) [1]. DTNs are networks which experience frequent disconnections between nodes, uncertainty of an end-to-end path, long one-way trip times, and may have high error rates and asymmetric links. Such networks exist in deep space satellite networks, very rural environments, disaster areas and underwater environments. In this work, we use machine learning classifiers to predict a set of neighboring nodes which are the most likely to deliver a message to a desired location based on message history delivery information.We use the Common Open Research Emulator (CORE) [2] to emulate the DTN environment based on real-world location traces and collect network traffic statistics from the Bundle Protocol implementation IBR-DTN [3]. The software architecture for classification-based routing, analysis and preparation of the network history data and prediction results are discussed.
Delay Tolerant Networks↗
Impacts of high resolution data on traveler compliance levels in emergency evacuation simulations
In this article, we conducted a comparison study of evacuation assignment based on Traffic Analysis Zones (TAZ) and high resolution LandScan USA Population Cells (LPC) with detailed real world roads network. A platform for evacuation modeling built on high resolution population distribution data and activity-based microscopic traffic simulation was proposed. This platform can be extended to any cities in the world. The results indicated that evacuee compliance behavior affects evacuation efficiency with traditional TAZ assignment, but it did not significantly compromise the performance with high resolution LPC assignment. The TAZ assignment also underestimated the real travel time during evacuation. This suggests that high data resolution can improve the accuracy of traffic modeling and simulation. The evacuation manager should consider more diverse assignment during emergency evacuation to avoid congestions.
97 MATHEMATICS AND COMPUTING↗
Netostat: analyzing dynamic flow patterns in high-speed networks
Understanding flow traffic patterns in networks, such as the Internet or service provider networks, is crucial to improving their design and building them robustly. However, as networks grow and become more complex, it is increasingly cumbersome and challenging to study how the many flow patterns, sizes and the continually changing source-destination pairs in the network evolve with time. Here, we present Netostat, a visualization-based network analysis tool that uses visual representation and a mathematics framework to study and capture flow patterns, using graph theoretical methods such as clustering, similarity and difference measures. Netostat generates an interactive graph of all traffic patterns in the network, to isolate key elements that can provide insights for traffic engineering. We present results for U.S. and European research networks, ESnet and GEANT, demonstrating network state changes, to identify major flow trends, potential points of failure, and bottlenecks.
97 MATHEMATICS AND COMPUTING↗
An Initial Investigation of the Design Challenges Associated with Reliable 100GigE Packet Capture
Network security researchers often rely on Emulytics TM to provide a way to evaluate the safety and security of real world systems. This work involves running a large number of virtual machines on a distributed platform to observe how software and hardware will respond to different types of attacks. While Emulytics TM software such as minimega provide a scalable system for conducting experiments, the sheer volume of network traffic produced in an experiment can easily exceed the rate at which data can be recorded for offline analysis. As such, researchers must perform live analytics, narrow their monitoring scope or accept that they must run an experiment multiple times to capture all the information they require. In support of Sandia's commitment to Emulytics TM , we are developing new storage components for the Carlin cluster that will enable researchers to capture significantly more network traffic from their experiments. This report provides a summary of Haoda Wang's initial investigation of how new AMD Epyc storage nodes can be adapted to perform packet capture at 100Gbps speeds with minimal loss. This work found that the NVMe storage capabilities of the Epyc architecture are suitable for capturing 100Gbps Ethernet traffic. While capturing traffic with existing libraries was surprisingly challenging, we were able to develop a DPDK-based software tool that recorded network traffic to disk with minimal packet loss.
97 MATHEMATICS AND COMPUTING↗
Defining Dynamic Route Structure
This poster describes a method for defining route structure from flight tracks. Dynamically generated route structures could be useful in guiding dynamic airspace configuration and helping controllers retain situational awareness under dynamically changing traffic conditions. Individual merge and diverge intersections between pairs of flights are identified, clustered, and grouped into nodes of a route structure network. Links are placed between nodes to represent major traffic flows. A parametric analysis determined the algorithm input parameters producing route structures of current day flight plans that are closest to todays airway structure. These parameters are then used to define and analyze the dynamic route structure over the course of a day for current day flight paths. Route structures are also compared between current day flight paths and more user preferred paths such as great circle and weather avoidance routing.
Zelinski, Shannon↗
Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks
The number and sophistication of cyberattacks on industries and governments have dramatically grown in recent years. To counter this movement, new advanced tools and techniques are needed to detect cyberattacks in their early stages such that defensive actions may be taken to avert or mitigate potential damage. From a cybersecurity analysis perspective, detecting cyberattacks may be cast as a problem of identifying patterns in computer network traffic. Logically and intuitively, these patterns may take on the form of a directed graph that conveys how an attack or intrusion propagates through the computers of a network. Such cyberattack graphs could provide cybersecurity analysts with powerful conceptual representations that are natural to express and analyze. We have been researching and developing graph-centric approaches and algorithms for dynamic cyberattack detection. The advanced dynamic graph algorithms we are developing will be packaged into a streaming network analysis framework known as StreamWorks. With StreamWorks, a scientist or analyst may detect and identify precursor events and patterns as they emerge in complex networks. This analysis framework is intended to be used in a dynamic environment where network data is streamed in and is appended to a large-scale dynamic graph. Specific graphical query patterns are decomposed and collected into a graph query library. The individual decomposed subpatterns in the library are continuously and efficiently matched against the dynamic graph as it evolves to identify and detect early, partial subgraph patterns. The scalable emerging subgraph pattern algorithms will match on both structural and semantic network properties.
Chin, George↗
Allosterically coupled conformational dynamics in solution prepare the sterol transfer protein StarD4 to release its cargo upon interaction with target membranes
Complex mechanisms regulate the cellular distribution of cholesterol, a critical component of eukaryote membranes involved in regulation of membrane protein functions directly and through the physiochemical properties of membranes. StarD4, a member of the steroidogenic acute regulator-related lipid-transfer (StART) domain (StARD)-containing protein family, is a highly efficient sterol-specific transfer protein involved in cholesterol homeostasis. Its mechanism of cargo loading and release remains unknown despite recent insights into the key role of phosphatidylinositol phosphates in modulating its interactions with target membranes. We have used large-scale atomistic Molecular dynamics (MD) simulations to study how the dynamics of cholesterol bound to the StarD4 protein can affect interaction with target membranes, and cargo delivery. We identify the two major cholesterol (CHL) binding modes in the hydrophobic pocket of StarD4, one near S136&S147 (the Ser-mode), and another closer to the putative release gate located near W171, R92&Y117 (the Trp-mode). We show that conformational changes of StarD4 associated directly with the transition between these binding modes facilitate the opening of the gate. To understand the dynamics of this connection we apply a machine-learning algorithm for the detection of rare events in MD trajectories (RED), which reveals the structural motifs involved in the opening of a front gate and a back corridor in the StarD4 structure occurring together with the spontaneous transition of CHL from the Ser-mode of binding to the Trp-mode. Further analysis of MD trajectory data with the information-theory based NbIT method reveals the allosteric network connecting the CHL binding site to the functionally important structural components of the gate and corridor. Mutations of residues in the allosteric network are shown to affect the performance of the allosteric connection. These findings outline an allosteric mechanism which prepares the CHL-bound StarD4 to release and deliver the cargo when it is bound to the target membrane.
59 BASIC BIOLOGICAL SCIENCES↗
Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach
Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.
Jin, Ling↗
Satellite B-ISDN traffic analysis
The impact of asynchronous transfer mode (ATM) traffic on the advanced satellite broadband integrated services digital network (B-ISDN) with onboard processing is reported. Simulation models were built to analyze the cell transfer performance through the statistical multiplexer at the earth station and the fast packet switch at the satellite. The effectiveness of ground ATM cell preprocessing was established, as well as the performance of several schemes for improving the down-link beam utilization when the space segment employs a fast packet switch.
Shyy, Dong-Jye↗
A communications model for an ISAS to NASA span link
The authors propose that an initial computer-to-computer communication link use the public packet switched networks (PPSN) Venus-P in Japan and TELENET in the U.S. When the traffic warrants it, this link would then be upgraded to a dedicated leased line that directly connects into the Space Physics Analysis Network (SPAN). The proposed system of hardware and software will easily support migration to such a dedicated link. It therefore provides a cost effective approach to the network problem. Once a dedicated line becomes operation it is suggested that the public networks link and continue to coexist, providing a backup capability.
Green, James L.↗
An Architectural Concept for Intrusion Tolerance in Air Traffic Networks
The goal of an intrusion tolerant network is to continue to provide predictable and reliable communication in the presence of a limited num ber of compromised network components. The behavior of a compromised network component ranges from a node that no longer responds to a nod e that is under the control of a malicious entity that is actively tr ying to cause other nodes to fail. Most current data communication ne tworks do not include support for tolerating unconstrained misbehavio r of components in the network. However, the fault tolerance communit y has developed protocols that provide both predictable and reliable communication in the presence of the worst possible behavior of a limited number of nodes in the system. One may view a malicious entity in a communication network as a node that has failed and is behaving in an arbitrary manner. NASA/Langley Research Center has developed one such fault-tolerant computing platform called SPIDER (Scalable Proces sor-Independent Design for Electromagnetic Resilience). The protocols and interconnection mechanisms of SPIDER may be adapted to large-sca le, distributed communication networks such as would be required for future Air Traffic Management systems. The predictability and reliabi lity guarantees provided by the SPIDER protocols have been formally v erified. This analysis can be readily adapted to similar network stru ctures.
Maddalon, Jeffrey M.↗
Navigation/traffic control satellite mission study. Volume 3 - Selected navigation/ traffic control satellite system analysis and equipment definition Final report
L band and VHF voice communication in satellite navigation and traffic control network
Source record↗
Criteria development for upgrading computer networks
Being an infrastructure system, the computer network has a fundamental role in the day to day activities of personnel working at KSC. It is easily appreciated that the lack of 'satisfactory' network performance can have a high 'cost' for KSC. Yet, this seemingly obvious concept is quite difficult to demonstrate. At what point do we say that performance is below the lowest tolerable level? How do we know when the 'cost' of using the system at the current level of degraded performance exceeds the cost of upgrading it? In this research, we consider the cost and performance factors that may have an effect in decision making in regards to upgrading computer networks. Cost factors are detailed in terms of 'direct costs' and 'subjective costs'. Performance factors are examined in terms of 'required performance' and 'offered performance.' Required performance is further examined by presenting a methodology for trend analysis based on applying interpolation methods to observed traffic levels. Offered performance levels are analyzed by deriving simple equations to evaluate network performance. The results are evaluated in the light of recommended upgrade policies currently in use for telephone exchange systems, similarities and differences between the two types of services are discussed.
Efe, Kemal↗
Graph Analytics and Optimization Methods for Insights from the Uber Movement Data
In this work we leverage the Uber movement dataset for the Los Angeles (LA) area where partial TAZ to TAZ (Traffic Analysis Zone) trip time data is available. We first create a TAZ-TAZ network based on nearest neighbors and propose a model that allows us to complete the $(O-D)$ (Origin-Destination) travel time matrix, using optimization methods such as non-negative least squares. We apply these algorithms for several communities in the TAZ-TAZ network and present insights in the form of completed $(O-D)$ matrices and associated temporal trends. We qualify the error performance and scalability of our flows. We conclude by pointing out the directions in our ongoing work to improve the quality and scale of travel time estimation.
Visweswara Sathanur, Arun↗
A Software Defined Network Design for Analyzing Streaming Data in Transit
Year after year, network traffic keeps reaching newhighs as unprecedented volumes of data flow between an ever-increasing number of sources and destinations. As part of the Analysis on the Wire project, we aim to develop a network-centric approach for streaming data processing to facilitate scientific data analysis and reduce the overhead in sending big data to a data center. This work discusses our design for programmable network devices to augment network capabilities for streaming data processing, including efforts in progress at Brookhaven National Laboratory and the challenges faced to date.
97 MATHEMATICS AND COMPUTING↗
Data communication network at the ASRM facility
This three-year project (February 1991 to February 1994) has involved analyzing and helping to design the communication network for the Advanced Solid Rocket Motor (ASRM) facility at Yellow Creek, near Iuka, MS. The principal concerns in the analysis were the bandwidth (both on average and in the worst case) and the expandability of the network. As the communication network was designed and modified, a careful evaluation of the bandwidth of the network, the capabilities of the protocol, and the requirements of the controllers and computers on the network was required. The overall network, which was heterogeneous in protocol and bandwidth, needed to be modeled, analyzed, and simulated to obtain some degree of confidence in its performance capabilities and in its performance under nominal and heavy loads. The results of our analysis did have an impact on the design and operation of the ASRM facility. During 1993 we analyzed many configurations of this basic network structure. The analyses are described in detail in Section 2 and 3 herein. Section 2 reports on an analysis of the whole network. The preliminary results of that research indicated that the most likely bottleneck as the network traffic increased would be the hubs. Thus a study of Cabletron hubs was initiated. The results of that study are in Section 3. Section 4 herein reports on the final network configuration analyzed. When the ASRM facility was mothballed in December of 1993, this was basically the planned and partially installed network. A briefing was held at NASA/MSFC on December 7, 1993, at which time our final analysis and conclusions were disseminated. This report contains a written record of most of the information disseminated at that briefing.
Moorhead, Robert J., III↗