An Information Centric Framework for Weather Sensing Data

Robert Thompson, Eric Lyons, Ishita Dasgupta, Spyridon Mastorakis, Michael Zink, Susmit Shannigrahi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Weather sensing and forecasting has become increasingly accurate in the last decade thanks to high-resolution radars, efficient computational algorithms, and high-performance computing facilities. Through a distributed and federated network of radars, scientists can make high-resolution observations of the weather conditions on a scale that benefits public safety, commerce, transportation, and other fields. While weather radars are critical infrastructure, they are often located in remote areas with poor network connectivity. Data retrieved from these radars are often delayed or lost, or even lack proper synchronization, resulting in sub-optimal weather prediction. This work applies Named Data Networking (NDN) to a federation of weather sensing radars for efficient content addressing and retrieval. We identify weather data based on a hierarchical naming scheme that allows us to explicitly access desired files. We demonstrate that compared to the window-based mechanism in TCP/IP, an NDN based mechanism improves data quality, reduces uncertainty, and enhances weather prediction.

Original languageEnglish (US)
Title of host publication2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665426718
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022 - Seoul, Korea, Republic of
Duration: May 16 2022May 20 2022

Publication series

Name2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
Volume2022-January

Conference

Conference2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
Country/TerritoryKorea, Republic of
CitySeoul
Period5/16/225/20/22

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Control and Optimization

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