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Storage I/O has become a performance bottleneck for many data grid applications. Characterization of I/O patterns has shown that many of these applications have complex, irregular I/O patterns. In this paper we show how stochastic Petri net (SPN) models can be exploited for performance analysis of hybrid I/O data grid storage systems. We study a typical storage system SPN modeling and simplify model complexities based on aggregate I/O. Evaluation using case studies shows that we can adjust the priority schedule by changing the ratio of file I/O and multimedia I/O.