1/4/2023 0 Comments Network radar key![]() ![]() McLaughlin, Director, Center for Collaborative Adaptive Sensing of the Atmosphere (CASA), College of Engineering, University of Massachusetts, Amherst, MA 01003, beam spreading. Distributed refers to the use of large numbers of small solid-state radars, spaced appropriately to overcome blockage due to the Earth’s curvature and improve resolution degradation caused Despite the use of large antennas, spatial broadening of the radar beam with increasing range prevents these systems from resolving structures on the sub-km scale over most of the coverage volume.ĭistributed Collaborative Adaptive Sensing (DCAS) is a new approach to radar sensing of the atmosphere being investigated to overcome the coverage limitations inherent in long-range radar networks. Long-range radars operate at wavelengths in the 5-10 cm range in order to minimize attenuation due to precipitation, and this necessitates the use of physically large antennas to achieve high spatial resolution. #NETWORK RADAR KEY FULL#This prevents the system from detecting the full vertical rotation of most tornadoes and can limit the accuracy of precipitation estimates near the surface. For example, the WSR-88D (NEXRAD) system is unable to view ~ 80% of the troposphere’s volume below 3 km altitude. Although the coverage of these radars is adequate for many situations, coverage at low altitudes far away from the radars is insufficient for many applications due to Earth’s curvature and terrain-induced blockage. Data collected by these sensors serve as critical inputs to weather-related decision making in many public and private sector functions (such as hazardous weather warning, transportation, agriculture, energy, among others) and new uses continue to develop as data dissemination and computational capabilities improve. Today’s weather observing radars are designed for long-range (up to hundreds of km) coverage with single-beam antennas designed to comprehensively map winds, precipitation, and other phenomena over large volumes of the mid- to upper- troposphere. Experimental results show that AWON-based application-aware services significantly improve the quality of the content delivered to the end users in bandwidth-constrained conditions. The effectiveness of the AWON architecture and the API is demonstrated for a real-time weather radar data dissemination application using planetlab. The API also enables communication between application and the overlay routing protocol for the desired QoS support. Application-defined plug-in modules are used to deploy application-specific functionality at each overlay node. The API supports the configuration of overlay nodes for in-network, application-aware processing. ![]() An application programming interface (API) is presented to facilitate development of applications within the AWON architectural framework. This paper presents an AWON (application-aware overlay networks) architecture for deploying application-aware services in an overlay network to best meet the application requirements over the available overlay networking infrastructure. The QoS requirements, e.g., required bandwidth, latency, acceptable data quality, and reliability are interdependent, and critical to the operation of these applications. ![]() Many real-time distributed collaborative applications are emerging that require exchange of critical sensor data among geographically distant end users under resource-constrained network conditions. ![]()
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