@inbook{7fb25c45106745df8e0378c68c3b0143,
title = "Modeling Techniques for Pool Depletion Systems",
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.",
keywords = "Closed Queueing Model, Depletion Time, Maximum Mean Absolute Percentage Error (MAPE), Place Wait, Subsystem Capacity",
author = "Davide Cerotti and Marco Gribaudo and Riccardo Pinciroli and Giuseppe Serazzi",
note = "Publisher Copyright: {\textcopyright} 2019, Springer International Publishing AG, part of Springer Nature.",
year = "2019",
doi = "10.1007/978-3-319-92378-9_6",
language = "English",
series = "EAI/Springer Innovations in Communication and Computing",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "79--94",
booktitle = "EAI/Springer Innovations in Communication and Computing",
address = "Germany",
}