Using Active Data to Provide Smart Data Surveillance to E-Science Users

Anthony Simonet, Kyle Chard, Gilles Fedak, Ian Foster
2015 2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing  
Modern scientific experiments often involve multiple storage and computing platforms, software tools, and analysis scripts. The resulting heterogeneous environments make data management operations challenging; the significant number of events and the absence of data integration makes it difficult to track data provenance, manage sophisticated analysis processes, and recover from unexpected situations. Current approaches often require costly human intervention and are inherently error prone. The
more » ... difficulties inherent in managing and manipulating such large and highly distributed datasets also limits automated sharing and collaboration. We study a real world e-Science application involving terabytes of data, using three different analysis and storage platforms, and a number of applications and analysis processes. We demonstrate that using a specialized data life cycle and programming model-Active Data-we can easily implement global progress monitoring, and sharing; recover from unexpected events; and automate a range of tasks.
doi:10.1109/pdp.2015.76 dblp:conf/pdp/SimonetCFF15 fatcat:7rkvxivepbhobdrqlovsgacwna