José Manuel Giménez-Guzmán

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We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction information in the session admission control process in mobile cellular networks. The novel technique is able to find better solutions and with less dispersion. The gain is obtained by(More)
SUMMARY We study the impact of incorporating handoff prediction information in the session admission control process in mobile cellular networks. We evaluate the performance of optimal policies obtained with and without the predictive information , while taking into account possible prediction errors. Two different approaches to compute the optimal(More)
In communication systems that guarantee seamless mobility of users across service areas, repeated attempts occur as a result of user behavior but also as automatic retries of blocked requests. Both phenomena play an important role in the system performance and therefore should not be ignored in its analysis. On the other hand, an exact Markovian model(More)
SUMMARY We study the problem of optimizing admission control policies in mobile multimedia cellular networks when pre-dictive information regarding movement is available and we evaluate the gains that can be achieved by making such predictive information available to the admission controller. We consider a general class of prediction agents which forecast(More)
In cellular networks, repeated attempts occur as result of user behavior but also as automatic retries of blocked requests. Both phenomena play an important role in the system performance and therefore should not be ignored in its analysis. On the other hand, an exact Markovian model analysis of such systems has proven to be infeasible and resorting to(More)
Admission control is one of the key traffic management mechanisms that must be deployed in order to meet the strict requirements on dependability imposed to the services provided by modern wireless networks. We study the problem of optimizing admission control policies in mobile multimedia cellular networks when predictive information regarding the movement(More)
Wireless technologies have rapidly evolved and are becoming ubiquitous. An increasing number of users attach to the Internet using these technologies; hence the performance of these wireless access links is a key point when considering the performance of the whole Internet. In this paper we present a measurement-based analysis of the performance of an IEEE(More)
We determine the gain that can be achieved by incorporating movement prediction information in the session admission control process in mobile cellular networks. The gain is obtained by evaluating the performance of optimal policies achieved with and without the predictive information, while taking into account possible prediction errors. We evaluate the(More)
Today, link-state routing protocols that compute multiple shortest paths predominate in data center and campus networks, where routing is performed either in layer three or in layer two using link-state routing protocols. But current proposals based on link-state routing do not adapt well to real time trac variations and become very complex when attempting(More)
In communication networks that guarantee seamless mobility of users across service areas, reattempts occur as a result of user behavior but also as automatic retries of blocked handovers. A multiserver system with two reattempt orbits is obtained when modeling these networks. However, an exact Markovian model analysis of such systems has proven to be(More)