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Advanced Resources Reservation in Mobile Cellular Networks: Static vs. Dynamic Approaches under Vehicular Mobility Model

by 1,2,* and 3
1
Department of Molecular Science and Nanosystems (DSMN), University Ca’ Foscari, Via Torino 155, Mestre, 30170 Venezia, Italy
2
Vysoka Skola Banska, Technical University of Ostrava, 17. Listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic
3
Department of Informatics Engineering, Modellistics, Electronics and Systems (DIMES), University of Calabria, Arcavacata di Rende, 87036 Rende, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Panagiotis Sarigiannidis
Telecom 2021, 2(4), 302-327; https://doi.org/10.3390/telecom2040020
Received: 16 May 2021 / Revised: 16 September 2021 / Accepted: 23 September 2021 / Published: 26 September 2021
Many studies in literature have shown that the bandwidth of an ongoing flow can dynamically change during multimedia sessions and an efficient bandwidth allocation scheme must be employed. This paper focuses its attention on the management of predictive services in Wireless Infrastructure Dynamic Networks. In particular, two classes of service are considered: NSIS-Mobility Independent Predictive and NSIS-Mobility Dependent Predictive, where NSIS is the Next Steps in Signaling protocol, employed for resources reservation in Integrated Services architectures. A general prediction technique is proposed, based both on the analysis of time spent into a cell by mobile nodes and on the probabilities of hand-in and hand-out events of mobile nodes from wireless cells. User mobility needs to be firstly analyzed and a novel realistic mobility model has been considered, differently from some existing works in which synthetic mobility is generated. The analysis of user mobility is mandatory when the reduction of passive resource reservations for NSIS-MIP users is desired, with a good enhancement in system utilization. Moreover, predictive reservation and admission control schemes have been integrated. The performance of the 2D wireless system is evaluated in terms of average system utilization, system outage probability, number of admitted flows and reservation prediction errors. We provided to carry out an extensive simulation campaign, in order to assess the goodness of the proposed idea: we verified that good results (in terms of perceived utility, bandwidth and admitted flows) can be obtained, outperforming also some existing works. View Full-Text
Keywords: CAC; bandwidth allocation; utility function; Markov model; path prediction; wireless networks CAC; bandwidth allocation; utility function; Markov model; path prediction; wireless networks
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MDPI and ACS Style

Fazio, P.; Tropea, M. Advanced Resources Reservation in Mobile Cellular Networks: Static vs. Dynamic Approaches under Vehicular Mobility Model. Telecom 2021, 2, 302-327. https://doi.org/10.3390/telecom2040020

AMA Style

Fazio P, Tropea M. Advanced Resources Reservation in Mobile Cellular Networks: Static vs. Dynamic Approaches under Vehicular Mobility Model. Telecom. 2021; 2(4):302-327. https://doi.org/10.3390/telecom2040020

Chicago/Turabian Style

Fazio, Peppino, and Mauro Tropea. 2021. "Advanced Resources Reservation in Mobile Cellular Networks: Static vs. Dynamic Approaches under Vehicular Mobility Model" Telecom 2, no. 4: 302-327. https://doi.org/10.3390/telecom2040020

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