@inproceedings{9ca07b0a149540ea81171fd2df46d3ec,
title = "Latency analysis of large volume satellite data transmissions",
abstract = "A wide array of time-sensitive satellite data is required in the research and development activities for natural hazard assessment, storms and weather prediction, hurricane tracking, disaster and emergency response, and so on. Identifying and analyzing the latencies of large volumes of real-time and near real-time satellite data is very useful and helpful for detecting transmission issues, managing IT resources, and configuring and optimizing data management systems. This paper introduces how to monitor and collect important timestamps of data transmissions, organize them in a NoSQL database, and explore data latency via a user-friendly dashboard. Taking Sentinel series satellite data as an example, data transmission issues are illustrated and investigated further. Latency analysis and explorations help data providers and managers improve data transmission and enhance data management.",
keywords = "Big Data, Data Latency, Data Quality, MongoDB, NoSQL, Satellite Data",
author = "Weiguo Han and Matthew Jochum",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 ; Conference date: 23-07-2017 Through 28-07-2017",
year = "2017",
month = dec,
day = "1",
doi = "10.1109/IGARSS.2017.8126976",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "384--387",
booktitle = "2017 IEEE International Geoscience and Remote Sensing Symposium",
address = "United States",
}