Radar networking in Collaborative Adaptive Sensing of Atmosphere: State of the art and research challenges

Abstract

Collaborative Adaptive Sensing of the Atmosphere (CASA), in which a network of small weather radars collaborates in real time, has emerged as the preferred alternative for accurately detecting and tracking hazardous weather phenomena such as tornados. We address data transport and multi-sensor data fusion solutions proposed in context of CASA, focusing on their ability to support streaming and data pull modes of radar data access. How CASA can leverage emerging technologies, such as Named Data Networking (NDN), virtualization, and cloud computing to meet the performance, quality of service, and resource utilization requirements in a scalable manner are addressed. Open issues and research challenges for realizing the true potential of large-scale CASA networks are considered.