- -

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: 2012 WINET - ...
Tamaño: 174.3Kb
Formato: PDF
Descripción: Versión del Autor.
Abrir
[Cerrado]
Nombre: 2012 WINET - ...
Tamaño: 1.148Mb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor
dc.contributor.author Martínez Bauset, Jorge es_ES
dc.contributor.author Giménez Guzmán, José Manuel es_ES
dc.contributor.author Pla, Vicent es_ES
dc.date.accessioned 2015-10-28T09:24:30Z
dc.date.available 2015-10-28T09:24:30Z
dc.date.issued 2012-08
dc.identifier.issn 1022-0038
dc.identifier.uri http://hdl.handle.net/10251/56626
dc.description.abstract The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision. © Springer Science+Business Media, LLC 2012. es_ES
dc.description.sponsorship The authors would like to thank the reviewers for their valuable comments that helped to improve the quality of the paper. This work has been supported by the Spanish Ministry of Education and Science and European Comission (30% PGE, 70% FEDER) under projects TIN2008-06739-C04-02 and TIN2010-21378-C02-02 and by Comunidad de Madrid through project S-2009/TIC-1468. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Wireless Networks es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Cellular network es_ES
dc.subject Channel reservation es_ES
dc.subject Predictive information es_ES
dc.subject Reinforcement learning es_ES
dc.subject Admission control policies es_ES
dc.subject Admission controllers es_ES
dc.subject Channel reservations es_ES
dc.subject Hand over es_ES
dc.subject Handover prediction es_ES
dc.subject Mobile multimedia es_ES
dc.subject Mobile terminal es_ES
dc.subject Multiservice wireless networks es_ES
dc.subject Optimal channels es_ES
dc.subject Optimum value es_ES
dc.subject Performance Gain es_ES
dc.subject Reinforcement learning approach es_ES
dc.subject Theoretical limits es_ES
dc.subject Access control es_ES
dc.subject Optimization es_ES
dc.subject Forecasting es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.title Robustness of optimal channel reservation using handover prediction in multiservice wireless networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11276-012-0423-6
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2008-06739-C04-02/ES/ADMISSION CONTROL IN MOBILE NETWORKS WITH RATE-ADAPTIVE STREAMS AND HIERARCHICAL ARCHITECTURE/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CAM//S2009%2FTIC-1468/ES/Integración de servicios multimedia de siguiente generación en la internet del futuro/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació es_ES
dc.description.bibliographicCitation Martínez Bauset, J.; Giménez Guzmán, JM.; Pla, V. (2012). Robustness of optimal channel reservation using handover prediction in multiservice wireless networks. Wireless Networks. 18(6):621-633. https://doi.org/10.1007/s11276-012-0423-6 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s11276-012-0423-6 es_ES
dc.description.upvformatpinicio 621 es_ES
dc.description.upvformatpfin 633 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 18 es_ES
dc.description.issue 6 es_ES
dc.relation.senia 228753 es_ES
dc.identifier.eissn 1572-8196
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Comunidad de Madrid es_ES
dc.description.references Ji, S., Chen, W., Ding, X., Chen, Y., Zhao, C., & Hu, C. (2010). Potential benefits of GPS/GLONASS/GALILEO integration in an urban canyon–Hong Kong. Journal of Navigation, 63(4), 681–693. es_ES
dc.description.references Soh, W., & Kim, H. (2006). A predictive bandwidth reservation scheme using mobile positioning and road topology information. IEEE/ACM Transactions on Networking, 14(5), 1078–1091. es_ES
dc.description.references Kwon, H., Yang, M., Park, A., & Venkatesan, S. (2008). Handover prediction strategy for 3G-WLAN overlay networks. In Proceedings: IEEE network operations and management symposium (NOMS) (pp. 819–822). es_ES
dc.description.references Huang, C., Shen, H., & Chuang, Y. (2010). An adaptive bandwidth reservation scheme for 4G cellular networks using flexible 2-tier cell structure. Expert Systems with Applications, 37(9), 6414–6420. es_ES
dc.description.references Wanalertlak, W., Lee, B., Yu, C., Kim, M., Park, S., & Kim, W. (2011). Behavior-based mobility prediction for seamless handoffs in mobile wireless networks. Wireless Networks, 17(3), 645–658. es_ES
dc.description.references Becvar, Z., Mach, P., & Simak, B. (2011). Improvement of handover prediction in mobile WiMAX by using two thresholds. Computer Networks, 55, 3759–3773. es_ES
dc.description.references Sgora, A., & Vergados, D. (2009). Handoff prioritization and decision schemes in wireless cellular networks: a survey. IEEE Communications Surveys and Tutorials, 11(4), 57–77. es_ES
dc.description.references Choi, S., & Shin, K. G. (2002). Adaptive bandwidth reservation and admission control in QoS-sensitive cellular networks. IEEE Transactions on Parallel and Distributed Systems, 13(9), 882–897. es_ES
dc.description.references Ye, Z., Law, L., Krishnamurthy, S., Xu, Z., Dhirakaosal, S., Tripathi, S., & Molle, M. (2007). Predictive channel reservation for handoff prioritization in wireless cellular networks. Computer Networks, 51(3), 798–822. es_ES
dc.description.references Abdulova, V., & Aybay, I. (2011). Predictive mobile-oriented channel reservation schemes in wireless cellular networks. Wireless Networks, 17(1), 149–166. es_ES
dc.description.references Ramjee, R., Nagarajan, R., & Towsley, D. (1997). On optimal call admission control in cellular networks. Wireless Networks, 3(1), 29–41. es_ES
dc.description.references Bartolini, N. (2001). Handoff and optimal channel assignment in wireless networks. Mobile Networks and Applications, 6(6), 511–524. es_ES
dc.description.references Bartolini, N., & Chlamtac, I. (2002). Call admission control in wireless multimedia networks. In Proceedings: Personal, indoor and mobile radio communications (PIMRC) (pp. 285–289). es_ES
dc.description.references Pla, V., & Casares-Giner, V. (2003). Optimal admission control policies in multiservice cellular networks. In Proceedings of the international network optimization conference (INOC) (pp. 466–471). es_ES
dc.description.references Chu, K., Hung, L., & Lin, F. (2009). Adaptive channel reservation for call admission control to support prioritized soft handoff calls in a cellular CDMA system. Annals of Telecommunications, 64(11), 777–791. es_ES
dc.description.references El-Alfy, E., & Yao, Y. (2011). Comparing a class of dynamic model-based reinforcement learning schemes for handoff prioritization in mobile communication networks. Expert Systems With Applications, 38(7), 8730–8737. es_ES
dc.description.references Gimenez-Guzman, J. M., Martinez-Bauset, J., & Pla, V. (2007). A reinforcement learning approach for admission control in mobile multimedia networks with predictive information. IEICE Transactions on Communications , E-90B(7), 1663–1673. es_ES
dc.description.references Sutton R., Barto A. G. (1998) Reinforcement learning: An introduction. The MIT press, Cambridge, Massachusetts es_ES
dc.description.references Busoniu, L., Babuska, R., De Schutter, B., & Ernst, D. (2010). Reinforcement learning and dynamic programming using function approximators. Boca Raton, FL: CRC Press. es_ES
dc.description.references Watkins, C., & Dayan, P. (1992). Q-learning. Machine learning, 8(3–4), 279–292. es_ES
dc.description.references Brown, T. (2001). Switch packet arbitration via queue-learning. Advances in Neural Information Processing Systems, 14, 1337–1344. es_ES
dc.description.references Proper, S., & Tadepalli, P. (2006). Scaling model-based average-reward reinforcement learning for product delivery. In Proceedings 17th European conference on machine learning (pp. 735–742). es_ES
dc.description.references Driessens, K., Ramon, J., & Gärtner, T. (2006). Graph kernels and Gaussian processes for relational reinforcement learning. Machine Learning, 64(1), 91–119. es_ES
dc.description.references Banerjee, B., & Stone, P. (2007). General game learning using knowledge transfer. In Proceedings 20th international joint conference on artificial intelligence (pp. 672–677). es_ES
dc.description.references Martinez-Bauset, J., Pla, V., Garcia-Roger, D., Domenech-Benlloch, M. J., & Gimenez-Guzman, J. M. (2008). Designing admission control policies to minimize blocking/forced-termination. In G. Ming, Y. Pan & P. Fan (Eds.), Advances in wireless networks: Performance modelling, analysis and enhancement (pp. 359–390). New York: Nova Science Pub Inc. es_ES
dc.description.references Biswas, S., & Sengupta, B. (1997). Call admissibility for multirate traffic in wireless ATM networks. In Proceedings IEEE INFOCOM (2, pp. 649–657). es_ES
dc.description.references Evans, J. S., & Everitt, D. (1999). Effective bandwidth-based admission control for multiservice CDMA cellular networks. IEEE Transactions on Vehicular Technology, 48(1), 36–46. es_ES
dc.description.references Gilhousen, K., Jacobs, I., Padovani, R., Viterbi, A., Weaver, L. A. J., & Wheatley, C. E., III. (1991). On the capacity of a cellular CDMA system. IEEE Transactions on Vehicular Technology, 40(2), 303–312. es_ES
dc.description.references Hegde, N., & Altman, E. (2006). Capacity of multiservice WCDMA networks with variable GoS. Wireless Networks, 12, 241–253. es_ES
dc.description.references Ben-Shimol, Y., Kitroser, I., & Dinitz, Y. (2006). Two-dimensional mapping for wireless OFDMA systems. IEEE Transactions on Broadcasting, 52(3), 388–396. es_ES
dc.description.references Gao, D., Cai, J., & Ngan, K. N. (2005). Admission control in IEEE 802.11e wireless LANs. IEEE Network, 19(4), 6–13. es_ES
dc.description.references Liu, T., Bahl, P., & Chlamtac, I. (1998). Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks. IEEE Journal on Selected Areas in Communications, 16(6), 922–936. es_ES
dc.description.references Hu, F., & Sharma, N. (2004). Priority-determined multiclass handoff scheme with guaranteed mobile qos in wireless multimedia networks. IEEE Transactions on Vehicular Technology, 53(1), 118–135. es_ES
dc.description.references Chan, J., & Seneviratne, A. (1999). A practical user mobility prediction algorithm for supporting adaptive QoS in wireless networks. In Proceedings IEEE international conference on networks (ICON) (pp. 104–111). es_ES
dc.description.references Jayasuriya, A., & Asenstorfer, J. (2002). Mobility prediction model for cellular networks based on the observed traffic patterns. In Proceedings of IASTED international conference on wireless and optical communication (WOC) (pp. 386–391). es_ES
dc.description.references Diederich, J., & Zitterbart, M. (2005). A simple and scalable handoff prioritization scheme. Computer Communications, 28(7), 773–789. es_ES
dc.description.references Rashad, S., Kantardzic, M., & Kumar, A. (2006). User mobility oriented predictive call admission control and resource reservation for next-generation mobile networks. Journal of Parallel and Distributed Computing, 66(7), 971–988. es_ES
dc.description.references Soh, W. -S., & Kim, H. (2003). QoS provisioning in cellular networks based on mobility prediction techniques. IEEE Communications Magazine, 41(1), 86 – 92. es_ES
dc.description.references Lott, M., Siebert, M., Bonjour, S., vonHugo, D., & Weckerle, M. (2004). Interworking of WLAN and 3G systems. Proceedings IEE Communications, 151(5), 507 – 513. es_ES
dc.description.references Sanabani, M., Shamala, S., Othman, M., & Zukarnain, Z. (2007). An enhanced bandwidth reservation scheme based on road topology information for QoS sensitive multimedia wireless cellular networks. In Proceedings of the 2007 international conference on computational science and its applications—Part II (ICCSA) (pp. 261–274). es_ES
dc.description.references Mahadevan, S. (1996). Average reward reinforcement learning: Foundations, algorithms, and empirical results. Machine Learning, 22(1–3), 159–196. es_ES
dc.description.references Puterman, M. L. (1994). Markov decision processes: Discrete stochastic dynamic programming. New York: Wiley. es_ES
dc.description.references Das, T. K., Gosavi, A., Mahadevan, S., & Marchalleck, N. (1999). Solving semi-markov decision problems using average reward reinforcement learning. Management Science, 45(4), 560–574. es_ES
dc.description.references Darken, C., Chang, J., & Moody, J. (1992). Learning rate schedules for faster stochastic gradient search. In Proceedings of the IEEE-SP workshop on neural networks for signal processing II. (pp. 3–12). es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem