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.

Modeling Techniques for Pool Depletion Systems

Cerotti D.;Gribaudo M.;Pinciroli R.;Serazzi G.
2019

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.
EAI/Springer Innovations in Communication and Computing
978-3-319-92377-2
978-3-319-92378-9
Closed Queueing Model
Depletion Time
Maximum Mean Absolute Percentage Error (MAPE)
Place Wait
Subsystem Capacity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1151148
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