U.S. Department of Energy Office of Scientific and Technical Information
The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks
Recent technological advances have reduced the complexity and cost of developing sensor networks for remote environmental monitoring. However, the challenges of acquiring, transmitting, storing, and processing remote environmental data remain significant. The transmission of large volumes of sensor data to a centralized location (i.e., the cloud) burdens network resources, introduces latency and jitter, and can ultimately impact user experience. Edge computing has emerged as a paradigm in which substantial storage and computing resources are located at the “edge” of the network. In this paper, we present an edge storage and computing framework leveraging commercially available components organized in a tiered architecture and arranged in a hub-and-spoke topology. The framework includes a popular distributed database to support the acquisition, transmission, storage, and processing of Internet-of-Things-based sensor network data in a field setting. We present details regarding the architecture, distributed database, embedded systems, and topology used to implement an edge-based solution. Lastly, a real-world case study (i.e., seismic) is presented that leverages the edge storage and computing framework to acquire, transmit, store, and process millions of samples of data per hour.
Sepulveda, Frank, et al. "The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks." Sensors, vol. 22, no. 10, May. 2022. https://doi.org/10.3390/s22103615
Sepulveda, Frank, Thangraj, Joseph Soloman, & Pulliam, Jay (2022). The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks. Sensors, 22(10). https://doi.org/10.3390/s22103615
Sepulveda, Frank, Thangraj, Joseph Soloman, and Pulliam, Jay, "The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks," Sensors 22, no. 10 (2022), https://doi.org/10.3390/s22103615
@article{osti_1867294,
author = {Sepulveda, Frank and Thangraj, Joseph Soloman and Pulliam, Jay},
title = {The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks},
annote = {Recent technological advances have reduced the complexity and cost of developing sensor networks for remote environmental monitoring. However, the challenges of acquiring, transmitting, storing, and processing remote environmental data remain significant. The transmission of large volumes of sensor data to a centralized location (i.e., the cloud) burdens network resources, introduces latency and jitter, and can ultimately impact user experience. Edge computing has emerged as a paradigm in which substantial storage and computing resources are located at the “edge” of the network. In this paper, we present an edge storage and computing framework leveraging commercially available components organized in a tiered architecture and arranged in a hub-and-spoke topology. The framework includes a popular distributed database to support the acquisition, transmission, storage, and processing of Internet-of-Things-based sensor network data in a field setting. We present details regarding the architecture, distributed database, embedded systems, and topology used to implement an edge-based solution. Lastly, a real-world case study (i.e., seismic) is presented that leverages the edge storage and computing framework to acquire, transmit, store, and process millions of samples of data per hour.},
doi = {10.3390/s22103615},
url = {https://www.osti.gov/biblio/1867294},
journal = {Sensors},
issn = {ISSN 1424-8220},
number = {10},
volume = {22},
place = {Switzerland},
publisher = {MDPI AG},
year = {2022},
month = {05}}
2018 International IEEE Conference and workshop in Óbuda on Electrical and Power Engineering (CANDO-EPE), 2018 International IEEE Conference and Workshop in Óbuda on Electrical and Power Engineering (CANDO-EPE)https://doi.org/10.1109/CANDO-EPE.2018.8601139
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