Enhancing Data Resiliency With Dual-Feed Telemetry
Description:
The Southern California Seismic Network (SCSN), operated by Caltech and USGS, records on average 256 events of M>=3.0 per year including aftershocks and one M>=6.0 every 3 years. The SCSN utilizes state of the art computing technologies to provide timely earthquake event notification, ShakeMap, and other data products. Because of its critical role providing real time data for public safety, the SCSN maintains a robust and resilient network of more than 350 digital strong motion and broadband seismic stations to achieve this goal. We also import real-time data for an additional 170 stations from partner networks. We use a variety of digital data communications, including cell modems, private microwave network, digital radios, satellite, and the Internet. This presentation describes how we use dual-feed telemetry to improve resiliency of data delivery.
At the SCSN, all our seismic dataloggers in the field are capable of continuous dual-feed telemetry, i.e., sending the same seismic data to multiple acquisition servers. To improve the resiliency of our network, we use two acquisition servers all the time to receive continuous data from most seismic stations. One acquisition server is in the data center in Pasadena, CA, while the other uses an Elastic Cloud Computing (EC2) instance provided by Amazon Web Services (AWS). All the 100 sample/second seismic data acquired are rapidly distributed in 1-second packets via multicast network protocol to the real-time AQMS (ANSS Quake Monitoring System) servers. We have redundant AQMS servers locally in Pasadena, and an EC2-based AQMS instance in AWS.
To accomplish data resiliency, both streams of the 100 sample/second seismic data from each dual-feed station are available continuously to all the AQMS servers. Each AQMS server uses the fastest 1-second data packet, between the local and cloud acquisition, for that specific dual-feed station. Each AQMS system can directly distribute products using Product Distribution Layer (PDL), email, and SMS, to USGS, FEMA, Cal OES, and other government agencies.
Session: Network Seismology: Recent Developments, Challenges and Lessons Learned [Poster Session]
Type: Poster
Date: 5/1/2024
Presentation Time: 08:00 AM (local time)
Presenting Author: Rayomand
Student Presenter: No
Invited Presentation:
Authors
Rayomand Bhadha Presenting Author Corresponding Author rayo@caltech.edu California Institute of Technology |
Michael Black mlb@caltech.edu California Institute of Technology |
Courtney Hoggro choggro@caltech.edu California Institute of Technology |
Tyler Hirata thirata@caltech.edu California Institute of Technology |
Allen Husker ahusker@caltech.edu California Institute of Technology |
Igor Stubailo stubailo@caltech.edu California Institute of Technology |
Michael Watkins mwatkins@caltech.edu California Institute of Technology |
Ellen Yu eyu@caltech.edu California Institute of Technology |
Marcos Alvarez malvarez@usgs.gov U.S. Geological Survey |
Glenn Biasi gbiasi@usgs.gov U.S. Geological Survey, Pasadena, California, United States |
Joseph S Jones jjones@usgs.gov U.S. Geological Survey, Pasadena, California, United States |
Enhancing Data Resiliency With Dual-Feed Telemetry
Session
Network Seismology: Recent Developments, Challenges and Lessons Learned