Abstract
The evolution of digital technologies and software applications has introduced a new computational paradigm that involves the concurrent processing of jobs taken from a large pool in systems with limited computational capacity. Pool Depletion Systems is a framework proposed to analyze this paradigm where an optimal admission policy for jobs allocation is adopted to improve the performance of the system. Markov analysis and discrete event simulation, two techniques adopted to study Pool Depletion Systems framework, may require a long time before providing results, especially when dealing with complex systems. For this reason, a fluid approximation technique is presented in this chapter; in fact, it can provide results in a very short time, slightly decreasing their accuracy.
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Notes
- 1.
It can be verified by checking if D 1A > D 2A and D 1B < D 2B.
- 2.
In closed queuing networks throughput and response time can be computed only with respect to a given/specific resource, the so-called reference station [9].
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Acknowledgements
This research was supported in part by the European Commission under the grant ANTAREX H2020 FET-HPC-671623.
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Cerotti, D., Gribaudo, M., Pinciroli, R., Serazzi, G. (2019). Modeling Techniques for Pool Depletion Systems. In: Puliafito, A., Trivedi, K. (eds) Systems Modeling: Methodologies and Tools. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-92378-9_6
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