Engineering topics

Lee, Danny

Publications and source records attributed to Lee, Danny.

4 records

DOE OSTI2017

Scaling the PuNDIT project for wide area deployments

In today’s world of distributed scientific collaborations, there are many challenges to providing reliable inter-domain network infrastructure. Network operators use a combination of active monitoring and trouble tickets to detect problems, but these are often ineffective at identifying issues that impact wide-area network users. Additionally, these approaches do not scale to wide area inter-domain networks due to unavailability of data from all the domains along typical network paths. The Pythia Network Diagnostic InfrasTructure (PuNDIT) project aims to create a scalable infrastructure for automating the detection and localization of problems across these networks. The project goal is to gather and analyze metrics from existing perfSONAR monitoring infrastructures to identify the signatures of possible problems, locate affected network links, and report them to the user in an intuitive fashion. Simply put, PuNDIT seeks to convert complex network metrics into easily understood diagnoses in an automated manner. We present our progress in creating the PuNDIT system and our status in developing, testing and deploying PuNDIT. We report on the project progress to-date, describe the current implementation architecture and demonstrate some of the various user interfaces it will support. We close by discussing the remaining challenges and next steps and where we see the project going in the future.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method

Purpose: The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. Methods: The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. Results: For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. Conclusions: This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1994

Regular Topologies for Gigabit Wide-Area Networks: Congestion Avoidance Testbed Experiments

This document is Volume 3 of the final technical report on the work performed by SRI International (SRI) on SRI Project 8600. The document includes source listings for all software developed by SRI under this effort. Since some of our work involved the use of ST-II and the Sun Microsystems, Inc. (Sun) High-Speed Serial Interface (HSI/S) driver, we have included some of the source developed by LBL and BBN as well. In most cases, our decision to include source developed by other contractors depended on whether it was necessary to modify the original code. If we have modified the software in any way, it is included in this document. In the case of the Traffic Generator (TG), however, we have included all the ST-II software, even though BBN performed the integration, because the ST-II software is part of the standard TG release. It is important to note that all the code developed by other contractors is in the public domain, so that all software developed under this effort can be re-created from the source included here.

Denny, Barbara A.↗

NASA NTRS1994

Congestion Avoidance Testbed Experiments

DARTnet provides an excellent environment for executing networking experiments. Since the network is private and spans the continental United States, it gives researchers a great opportunity to test network behavior under controlled conditions. However, this opportunity is not available very often, and therefore a support environment for such testing is lacking. To help remedy this situation, part of SRI's effort in this project was devoted to advancing the state of the art in the techniques used for benchmarking network performance. The second objective of SRI's effort in this project was to advance networking technology in the area of traffic control, and to test our ideas on DARTnet, using the tools we developed to improve benchmarking networks. Networks are becoming more common and are being used by more and more people. The applications, such as multimedia conferencing and distributed simulations, are also placing greater demand on the resources the networks provide. Hence, new mechanisms for traffic control must be created to enable their networks to serve the needs of their users. SRI's objective, therefore, was to investigate a new queueing and scheduling approach that will help to meet the needs of a large, diverse user population in a "fair" way.

Denny, Barbara A.↗