Near Real-Time Parallel Processing and Advanced Data Management of SAR Images in Grid Environments

In this paper, we describe the process of parallelizing an existing, production level, sequential Synthetic Aperture Radar (SAR) processor based on the Range-Doppler algorithmic approach. We show how, taking into account the constraints imposed by the software architecture and related software engineering costs, it is still possible with a moderate programming effort to parallelize the software and present an message-passing interface (MPI) implementation whose speedup is about 8 on 9 processors, achieving near real-time processing of raw SAR data even on a moderately aged parallel platform. Moreover, we discuss a hybrid two-level parallelization approach that involves the use of both MPI and OpenMP. We also present GridStore, a novel data grid service to manage raw, focused and post-processed SAR data in a grid environment. Indeed, another aim of this work is to show how the processed data can be made available in a grid environment to a wide scientific community, through the adoption of a data grid service providing both metadata and data management functionalities. In this way, along with near real-time processing of SAR images, we provide a data grid-oriented system for data storing, publishing, management, etc.