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I have to write a system that has several data processing steps, each varying in time complexity. I intend to make use of buffer queues and multithreading for each preprocessing step. I have limited number of processes (each process can be seen as a server), and memory, so the buffer queues cannot be infinite. This seems like a perfect setting to use queueing models.

However, queueing models assume markov properties for input data, as I recall they also assume the input to follow poisson distribution.

So my question is, is it okay to assume those to model the data pipeline using queueing models?

Thank you.

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  • $\begingroup$ Not all of queueing theory assumes Poisson arrival process. $\endgroup$ – Mark L. Stone Jul 14 '18 at 14:43

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