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Autonomous Data Error Detection and Recovery in Streaming Applications
2013
Procedia Computer Science
Detecting and recovering from errors in data streams is paramount to developing successful autonomous real-time streaming applications. In this paper, we devise a multi-modal data error detection and recovery architecture to enable automated recovery from data errors in streaming applications based on available redundancy. We formally define error signatures as a way to identify classes of abnormal conditions and mode likelihood vectors as a quantitative discriminator of data stream condition
doi:10.1016/j.procs.2013.05.373
fatcat:yy7nmiimkvdarlfkmiaglqz754