Distributed, multi-user, multi-application, and multi-sensor data fusion over named data networks

Abstract

Named Data Networking (NDN) routes data based on their application-layer content names enabling location independence, in-network caching, and enhanced security. A proof-of-concept solution is presented that demonstrates the applicability of NDN for multi-user, multi-application, and multi-sensor data-fusion systems. The system consists of a collaborative network of weather radars name data based on their geographic location and weather feature (e.g., reflectivity of clouds and wind velocity). This enables end users to specify an area of interest for a particular weather feature while being oblivious to the placement of radars and associated computing facilities. Conversely, the data-fusion system can also use its knowledge about the underlying system to decide the best sensing and data processing strategies. Such sensor-independent names also enhance resilience, enable processing data close to the source, and benefit from NDN features such as in-network caching and duplicate query suppression, consequently reducing the bandwidth requirements of the entire data-fusion system. The solution is implemented as an overlaid NDN enabling the benefits of both the NDN and overlay networks. Simulation-based analysis using reflectivity data from an actual weather event showed 84% reduction in peak bandwidth consumption of radars and 95% reduction in peak query resolution latency.