A task-level adaptive MapReduce framework for real-time streaming data in healthcare applications
We propose a task-level adaptive MapReduce framework for healthcare applications. We prove the optimal runtime Map and Reduce task count when workload changes. Our method extends the MapReduce programming model to process streaming data. Our method also includes two methods to predict streaming data workload in run time. We demonstrate the effectiveness of the method on real-life workload benchmark.
adaptive mapreduce big data healthcare scientific applications kalman filter parallel processing