Predictive Timely Trigger and Performance Optimization for Deterministic Handovers

  • Ming Tao
  • Fagui Liu
  • Chao Qu


Pre-registration as an important feature in FIMPv6, ensures providing the continuous mobility services for the end-users roaming across heterogeneous wireless networks, and is achieved by obtaining the timely and precise link layer (L2) trigger in the handover preparation. Firing the L2 trigger in the timely manner for deterministic handovers hence is crucial for guaranteeing the handover performance, but difficult to be achieved in the practical application scenarios. The late L2 trigger causes a missed detection deteriorating the quality of service perceived by the mobile node. To address this issue, taking the measured received signal strength (RSS) as the evaluated index, a predictive model based on the combination of Empirical Mode Decomposition and Support Vector Regression is proposed to predict the RSS values for timely firing the event of handover trigger, and then the performance optimization is further designed with the assistant of the predictive trigger. With an appropriate implementation of the predictive trigger model, the accuracy is compared with the representative time series predictive model, and the efficiency has been verified by the simulations conducted on the NS-2 platform.


FMIPv6 L2 trigger RSS Predictive trigger model Performance optimization 



This study is supported by National Natural Science Fund, China (Grant No. 61300198), Guangdong Province Natural Science Foundation (S2013040016582), Guangdong Higher School Scientific Innovation Project (Nos. 2013KJCX0177 & 2014KTSCX188), Fundamental Research Funds for the Central Universities (SCUT 2014ZB0029), and China Postdoctoral Science Foundation (No. 2014M552199).


  1. 1.
    R. Koodli, Mobile IPv6 Fast Handovers, IETF RFC 5568, 2009.Google Scholar
  2. 2.
    Y. H. Han, H. Jang, J. H. Choi, et al., A Cross-Layering Design for IPv6 Fast Handover Support in an IEEE 802.16e wireless LAN, IEEE Network, Vol. 21, No. 6, pp. 54–62, 2006.CrossRefGoogle Scholar
  3. 3.
    W. P. L. Cully, S. L. Cotton and W. G. Scanlon, Empirical Performance of RSSI-Based Monte Carlo Localisation for Active RFID Patient Tracking Systems, International Journal of Wireless Information Networks, Vol. 19, No. 3, pp. 173–184, 2012.CrossRefGoogle Scholar
  4. 4.
    Y. Ye, P. Swar, K. Pahlavan and K. Ghaboosi, Accuracy of RSS-Based RF Localization in Multi-capsule Endoscopy, International Journal of Wireless Information Networks, Vol. 19, No. 3, pp. 229–238, 2012.CrossRefGoogle Scholar
  5. 5.
    J. Raiyn, Handoff self–management based on SNR in mobile communication networks, International Journal of Wireless and Mobile Computing, Vol. 6, No. 1, pp. 39–48, 2013.CrossRefGoogle Scholar
  6. 6.
    S. Chien, H. Liu, A. L. Y Low, et al, Smart Predictive Trigger for Effective Handover in Wireless Networks, Proceedings of IEEE Conf. Communications (ICC), pp. 2175–2181, 2008.Google Scholar
  7. 7.
    B. J. Chang, J. F. Chen, C. H. Hsieh, et al, Markov decision process-based adaptive vertical handover with RSS prediction in heterogeneous wireless networks, Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6, 2009.Google Scholar
  8. 8.
    Y. Luo, P. N. Tran, C. An, et al, Handover prediction for wireless networks in office environments using Hidden Markov Model, Proceedings of IFIP Wireless Days, pp. 1–7, 2013.Google Scholar
  9. 9.
    Y. Luo, P. N. Tran, C. An, et al, A Novel Handover Prediction Scheme in Content Centric Networking using Nonlinear Autoregressive Exogenous Model, Proceedings of IEEE Vehicular Technology Conference-Spring, pp. 1–5, 2013.Google Scholar
  10. 10.
    J. Yan, L. Zhao, J. Li, A Prediction-Based Handover Trigger Time Selection Strategy in Varying Network Overlapping Environment, Proceedings of IEEE Vehicular Technology Conference-Fall, pp. 1–5, 2011.Google Scholar
  11. 11.
    J. Park and Y. Lim, A Handover Prediction Model and its Application to Link Layer Triggers for Fast Handover, Wireless Personal Communications, Vol. 53, No. 3, pp. 501–516, 2010.CrossRefGoogle Scholar
  12. 12.
    S. Kunarak, R. Suleesathira, Predictive RSS with fuzzy logic based vertical handoff algorithm in heterogeneous wireless networks, Proceedings of International Symposium on Communications and Information Technologies, pp. 1235–1240, 2010.Google Scholar
  13. 13.
    S. Mohanty and I. F. Akyildiz, A Cross-Layer (Layer 2 + 3) Handover Management Protocol for Next-Generation Wireless Systems, IEEE Trans. Mobile Computing, Vol. 5, No. 10, pp. 1347–1360, 2006.CrossRefGoogle Scholar
  14. 14.
    M. Tao, H. Yuan, S. Dong, et al., Initiative Movement Prediction Assisted Adaptive Handover Trigger Scheme in Fast MIPv6, Computer Communications, Vol. 35, No. 10, pp. 1272–1282, 2012.CrossRefGoogle Scholar
  15. 15.
    W. Su, S. J. Lee, M. Gerla, Mobility prediction in wireless networks, Proceedings of IEEE 21st Century Military Communications Conference (MILCOM), Vol. 1, pp. 491–495, 2000.Google Scholar
  16. 16.
    J. Montavont, T. Noel, IEEE 802.11 handovers assisted by GPS information, Proceedings of IEEE Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 166–172, 2006.Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.School of ComputerDongguan University of TechnologyDongguanChina
  2. 2.School of Computer Science and EngineeringSouth China University of TechnologyGuangzhouChina

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