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

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

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Martínez Bauset, J.; Gimenez Guzman, JM.; Pla, V. (2012). Robustness of optimal channel reservation using handover prediction in multiservice wireless networks. Wireless Networks. 18(6):621-633. doi:10.1007/s11276-012-0423-6

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Title: Robustness of optimal channel reservation using handover prediction in multiservice wireless networks
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació
Issued date:
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 ...[+]
Subjects: Cellular network , Channel reservation , Predictive information , Reinforcement learning , Admission control policies , Admission controllers , Channel reservations , Hand over , Handover prediction , Mobile multimedia , Mobile terminal , Multiservice wireless networks , Optimal channels , Optimum value , Performance Gain , Reinforcement learning approach , Theoretical limits , Access control , Optimization , Forecasting
Copyrigths: Reserva de todos los derechos
Source:
Wireless Networks. (issn: 1022-0038 ) (eissn: 1572-8196 )
DOI: 10.1007/s11276-012-0423-6
Publisher:
Springer Verlag (Germany)
Publisher version: http://dx.doi.org/10.1007/s11276-012-0423-6
Thanks:
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 ...[+]
Type: Artículo

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.

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.

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). [+]
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.

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.

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).

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.

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.

Becvar, Z., Mach, P., & Simak, B. (2011). Improvement of handover prediction in mobile WiMAX by using two thresholds. Computer Networks, 55, 3759–3773.

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.

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.

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.

Abdulova, V., & Aybay, I. (2011). Predictive mobile-oriented channel reservation schemes in wireless cellular networks. Wireless Networks, 17(1), 149–166.

Ramjee, R., Nagarajan, R., & Towsley, D. (1997). On optimal call admission control in cellular networks. Wireless Networks, 3(1), 29–41.

Bartolini, N. (2001). Handoff and optimal channel assignment in wireless networks. Mobile Networks and Applications, 6(6), 511–524.

Bartolini, N., & Chlamtac, I. (2002). Call admission control in wireless multimedia networks. In Proceedings: Personal, indoor and mobile radio communications (PIMRC) (pp. 285–289).

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).

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.

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.

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.

Sutton R., Barto A. G. (1998) Reinforcement learning: An introduction. The MIT press, Cambridge, Massachusetts

Busoniu, L., Babuska, R., De Schutter, B., & Ernst, D. (2010). Reinforcement learning and dynamic programming using function approximators. Boca Raton, FL: CRC Press.

Watkins, C., & Dayan, P. (1992). Q-learning. Machine learning, 8(3–4), 279–292.

Brown, T. (2001). Switch packet arbitration via queue-learning. Advances in Neural Information Processing Systems, 14, 1337–1344.

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).

Driessens, K., Ramon, J., & Gärtner, T. (2006). Graph kernels and Gaussian processes for relational reinforcement learning. Machine Learning, 64(1), 91–119.

Banerjee, B., & Stone, P. (2007). General game learning using knowledge transfer. In Proceedings 20th international joint conference on artificial intelligence (pp. 672–677).

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.

Biswas, S., & Sengupta, B. (1997). Call admissibility for multirate traffic in wireless ATM networks. In Proceedings IEEE INFOCOM (2, pp. 649–657).

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.

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.

Hegde, N., & Altman, E. (2006). Capacity of multiservice WCDMA networks with variable GoS. Wireless Networks, 12, 241–253.

Ben-Shimol, Y., Kitroser, I., & Dinitz, Y. (2006). Two-dimensional mapping for wireless OFDMA systems. IEEE Transactions on Broadcasting, 52(3), 388–396.

Gao, D., Cai, J., & Ngan, K. N. (2005). Admission control in IEEE 802.11e wireless LANs. IEEE Network, 19(4), 6–13.

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.

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.

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).

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).

Diederich, J., & Zitterbart, M. (2005). A simple and scalable handoff prioritization scheme. Computer Communications, 28(7), 773–789.

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.

Soh, W. -S., & Kim, H. (2003). QoS provisioning in cellular networks based on mobility prediction techniques. IEEE Communications Magazine, 41(1), 86 – 92.

Lott, M., Siebert, M., Bonjour, S., vonHugo, D., & Weckerle, M. (2004). Interworking of WLAN and 3G systems. Proceedings IEE Communications, 151(5), 507 – 513.

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).

Mahadevan, S. (1996). Average reward reinforcement learning: Foundations, algorithms, and empirical results. Machine Learning, 22(1–3), 159–196.

Puterman, M. L. (1994). Markov decision processes: Discrete stochastic dynamic programming. New York: Wiley.

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.

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).

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