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In this paper, we explore the complexity of mapping filtering streaming applications on large-scale homogeneous and heterogeneous platforms, with a particular emphasis on communication models and their impact. Filtering applications are streaming applications where each node also has a selectivity which either increases or decreases the size of its input data set. This selectivity makes the problem of scheduling these applications more challenging than the more studied problem of scheduling “non-filtering” streaming workflows. We address the complexity of the following two problems:

• Evaluation: Given a mapping of nodes to processors, how can one compute the period and latency?
• Optimization: Given a filtering workflow, how can one compute the mapping and schedule that minimize the period or latency? A solution to this problem requires …