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Search Publications by: David W. Griffith (Fed)

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Displaying 1 - 25 of 90

National Institute of Standards and Technology Environmental Scan 2023: Societal and Technology Landscape to Inform Science and Technology Research

August 23, 2023
Author(s)
Ashley Boggs-Russell, Kerrianne Buchanan, David W. Griffith, Heather Evans, Dimitrios Meritis, Lisa Ng, Anna Sberegaeva, Michelle Stephens
The 2023 National Institute of Standards and Technology Environmental Scan provides an analysis of key external factors that could impact NIST and the fulfillment of its mission in coming years. The analyses were conducted through three separate lenses

An Overview of Advances in Signal Processing Techniques for Classical and Quantum Wideband Synthetic Apertures

March 28, 2023
Author(s)
Peter Vouras, Kumar Vijay Mishra, Aly Artusio-Glimpse, Samuel Pinilla, Angeliki Xenaki, David W. Griffith, Karen Egiazarian
Rapid developments in synthetic aperture (SA) systems, which generate a larger aperture with greater angular resolution than is inherently possible from the physical dimensions of a single sensor alone, are leading to novel research avenues in several

Towards Generative Adversarial Network on Industrial Internet of Things

October 1, 2022
Author(s)
Cheng Qian, Wei Yu, Chao Lu, David W. Griffith, Nada T. Golmie
Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is one critical issue for applying machine learning in Industrial Internet of Things (IIoT) systems

Towards an Integrated Simulation Platform for Internet of Vehicles

August 11, 2022
Author(s)
Xing Liu, Wei Yu, Cheng Qian, David W. Griffith, Nada T. Golmie
The interconnection and digitization of the physical world has increased dramatically with the widespread deployment of network communication and the rapid development of the Internet of Things (IoT). Application scenarios and requirements in IoT are more

Survey of Graph Neural Networks and Applications

July 28, 2022
Author(s)
Fan Liang, Cheng Qian, Wei Yu, David W. Griffith, Nada T. Golmie
The advance of deep learning has shown great potential in applications (speech, image and video classification). In these applications, deep learning models are trained by datasets in Euclidean space with fixed dimensions and sequences. Nonetheless, the

5G NR and LTE Coexistence in Public Safety Communications

May 27, 2022
Author(s)
Sneihil Gopal, David W. Griffith
5G New Radio (NR) offers the promise of supporting new Public Safety Communications (PSC) services. Since the majority of the frequency bands worldwide are used by 4th Generation (4G) Long Term Evolution (LTE) and because options such as acquiring new

Deep Learning Based Link-Level Abstraction for mmWave Communications

November 18, 2021
Author(s)
Jian Wang, Neeraj Varshney, Jiayi Zhang, David W. Griffith, Nada T. Golmie
Link abstraction is an efficient way for predicting link-level performance (e.g., whether the receiver successfully receives packets through communication links). It can be used to support system-level simulation and facilitate link adaption. Nonetheless

2019 Public Safety Broadband Stakeholder Presentations by NIST Authors

October 25, 2021
Author(s)
Richard A. Rouil, Tom Henderson, Marco Mezzavilla, Michele Polese, Jaden Pieper, Chunmei Liu, Silas Thompson, David W. Griffith, Christopher Walton, Christopher D. Dennis, Fabio C. da Silva, John S. Garofolo, James M. Horan, Samuel Hood, Julie Stroup, Christine Task, Terese Manley, Sam Ray, Alison Kahn, Maxwell Maurice, Hien V. Nguyen, Frederick R. Byers, Kristen K. Greene, Mary Theofanos, Yee-Yin Choong, Sandra Spickard Prettyman, Pamela J. Konkol, Jeffrey Cichonski, Bill Fisher, Gema Howell, Mike Dolan, Adam Lewis, Michael Ogata, John Beltz, Michael Bartock, Sarah Hughes, Santosh Rajvaidya, Craig Connelly, Scott Ledgerwood, Megan Waldock, Dereck R. Orr, Donald Bradshaw, Jeb Benson
2019 Public Safety Broadband Stakeholder Presentations by NIST Authors

Towards An Adaptive Time-Triggered Protocol in Wireless Networks

October 19, 2021
Author(s)
Jin Zhang, Fan Liang, Wei Yu, David W. Griffith, Wenqi Guo, Avi Gopstein
Time sensitive activities occur extensively in industrial Internet of Things (IoT) environments. Classical time-triggered protocols in wired networks, such as Ethernet, have been proven effective in supporting real-time and safety-critical communications

Towards Online Continuous Reinforcement Learning on Industrial Internet of Things

October 19, 2021
Author(s)
Cheng Qian, Wei Yu, Xing Liu, David W. Griffith, Nada T. Golmie
In Industrial Internet of Things (IIoT), the information and communication technologies powered by IoT can greatly improve the efficiency and timeliness of information exchange between different industrial components. Likewise, machine learning techniques

Towards Deep Q-Network Based Resource Allocation in Industrial Internet of Things

June 29, 2021
Author(s)
Fan Liang, Wei Yu, Xing Liu, David W. Griffith, Nada T. Golmie
With the increasing adoption of Industrial Internet of Things (IIoT) devices, infrastructures, and supporting applications, it is critical to design schemes to effectively allocate resources (e.g., networking, computing, and energy) in IIoT systems

Study of 5G New Radio (NR) Support for Direct Mode Communications

May 7, 2021
Author(s)
Fernando Cintron, David W. Griffith, Chunmei Liu, Richard A. Rouil, Yishen Sun, Jian Wang, Peng Liu, Chen Shen, Aziza Ben Mosbah, Samantha Gamboa Quintiliani
In public safety communications, direct mode communication is essential to keep first responders connected, especially when there is no network coverage. Direct mode communication is supported in Third Generation Partnership Project (3GPP) Long Term

UE-to-Network Relay Model B Discovery in ProSe-Enabled LTE Networks

April 6, 2021
Author(s)
Alexandre C. Moreaux, Samantha Gamboa Quintiliani, David W. Griffith, Richard A. Rouil
In this paper, we expand previous analytical models to offer a more complete representation of Model B ProSe direct discovery. Using these models, we can obtain performance metrics such as the average time a given Remote User Equipment (UE) takes to

Towards Deep Transfer Learning in Industrial Internet of Things

February 26, 2021
Author(s)
Xing Liu, Wei Yu, Fan Liang, David Griffith, Nada T. Golmie
In this paper, we propose a general framework to adopt transfer learning in IIoT systems. Transfer learning is a machine learning technique that fully uses the knowledge from pre- trained models to reduce the computing requirements for the training process

On Deep Reinforcement Learning Security for Industrial Internet of Things

February 15, 2021
Author(s)
Xing Liu, Wei Yu, Fan Liang, David W. Griffith, Nada T. Golmie
Industrial Internet of Things (IIoT), also known as Industry 4.0, empowers manufacturing and production processes by leveraging automation and Internet of Things (IoT) technologies. In IIoT, the information communication technologies enabled by IoT could

Towards Computing Resource Reservation Scheduling in Industrial Internet of Things

December 11, 2020
Author(s)
Fan Liang, Wei Yu, Xing Liu, David W. Griffith, Nada T. Golmie
The Industrial Internet of Things (IIoT) is a critically important implementation of the Internet of Things (IoT), connecting IoT devices ubiquitously in an industrial environment. Based on the interconnection of IoT devices, IIoT applications can collect

On Data Integrity Attacks against Industrial Internet of Things

August 24, 2020
Author(s)
Hansong Xu, Wei Yu, Xing Liu, David W. Griffith, Nada T. Golmie
Industrial Internet of Things (IIoT) is predicted to drive the fourth industrial revolution through massive interconnection of industrial devices, such as sensors, controllers and actuators, integrating advances in smart machinery and data analytics driven

UE-to-Network Relay Discovery in ProSe-enabled LTE Networks

March 30, 2020
Author(s)
Samantha M. Gamboa Quintiliani, Alexandre C. Moreaux, David W. Griffith, Richard A. Rouil
The UE-to-Network Relay functionality was introduced to Long Term Evolution (LTE) cellular networks in Release 13. In this technology, User Equipment (UEs) acting as Relay UEs are used to extend network coverage to cell-edge and out-of-coverage Remote UEs

On Selecting Channel Parameters for Public Safety Network Applications in LTE Direct

March 26, 2020
Author(s)
Siyuan Feng, Hyong-Ah Choi, David W. Griffith, Richard A. Rouil
The Third Generation Partnership Project (3GPP) defines various pre-configured channel parameters for the Long- Term Evolution (LTE) Device-to-Device (D2D) communications with Physical Sidelink (SL) Channels. In this paper, we investigate the impacts of

On Upper Bounds for D2D Group Size

February 27, 2020
Author(s)
David W. Griffith, Aziza Ben Mosbah
In this paper, we examine the Physical Sidelink Discovery Channel (PSDCH) for out-of-coverage (OOC) Device-to-Device (D2D) Long Term Evolution (LTE) networks using direct discovery for User Equipments (UEs) that are half-duplex. We derive upper bounds for

Towards Edge-Based Deep Learning in Industrial Internet of Things

January 1, 2020
Author(s)
Fan Liang, Wei Yu, Xing Lu, David W. Griffith, Nada T. Golmie
As a typical application of the Internet of Things (IoT), the Industrial Internet of Things (I- IoT) connects all the related IoT sensing and actuating devices ubiquitously so that the monitoring and control of numerous industrial systems can be realized

A Deep Learning-Based Weather Forecast System for Data Volume and Recency Analysis

February 18, 2019
Author(s)
Jarrett Booz, Wei Yu, Guobin Xu, David W. Griffith, Nada T. Golmie
Accurate weather forecast is important to our daily life. Through physical atmospheric models, the weather can be accurately forecasted in a short period time. To provide weather forecast, machines learning techniques can be used for understanding and

Performance Assessment of Smart Meter Traffic over LTE Network Using SDR Testbed

February 18, 2019
Author(s)
Amirshahram Hematian, Wei Yu, David W. Griffith, Nada T. Golmie
In the smart grid, a variety of smart meters will be deployed to support diverse services, such as energy distribution management, grid monitoring and management, and the integration of renewable energy resources. On the power distribution side, regular