OPTIMISATION OF HANDOFF PERFORMANCE IN WIRELESS NETWORKS USING EVOLUTIONARY ALGORITHMS

Suresh Venkatachalaiah, Richard J. Harris

Abstract

In this paper we propose to improve handoff performance by applying a mobility prediction technique, which is optimised using evolutionary algorithms such as genetic algorithm and particle swarm optimisation. Here, we describe a hybrid technique that uses the Grey model in combination with fuzzy logic and evolutionary algorithms. Handoff is the call handling mechanism invoked when a mobile node moves from one cell to another and the accuracy in predicting mobility holds a key to handoff performance. Our model uses the received signal strength from the base stations to help the mobile device during handoff. We also describe the optimisation criterion adopted in this paper and compare the self-tuning algorithm and the two evolutionary algorithms in terms of accuracy and faster convergence time. The improved accuracy of the approaches is shown by comparing results of simulations and experiments.

References

  1. Chellappa, R., Jennings, A., and Shenoy, N. (2003). Route discovery and reconstruction in mobile ad hoe networks. In Networks, 2003. ICON2003. The 11th IEEE International Conference on, pages 549-554.
  2. Deng, J. L. (1989). Introduction to grey system theory. J. Grey Syst., 1(1):1-24.
  3. Hwang, C.-L. (2004). A novel takagi-sugeno-based robust adaptive fuzzy sliding-mode controller. Fuzzy Systems, IEEE Transactions on, 12(5):676-687.
  4. James Kennedy, J. and R.C., E. (2001). Swarm Intelligence. Morgan Kaufmann Publishers, san Francisco,CA.
  5. Janacek, G. and Swift, L. (1993). Time series Forecasting, Simulation, Applications. Ellis Horwood, Great Britain.
  6. Krink, T., Vesterstrom, J., and Riget, J. (2002). Particle swarm optimisation with spatial particle extension. In Evolutionary Computation, 2002. CEC 7802. Proceedings of the 2002 Congress on, volume 2, pages 1474- 1479.
  7. Kung, C.-C. and Lai, W.-C. (1999). ga - based design of a region-wise fuzzy sliding mode controller. In Electrical and Computer Engineering, 1999 IEEE Canadian Conference on, volume 2, pages 971-976 vol.2.
  8. Maeda, M. and Miyajima, H. (2002). Constructive methods of fuzzy rules for function approximation. In IThe 2002 International Technical Conference On Circuits/Systems,Computers and Communications, Phuket, Thailand.
  9. Man, K. F. K. F. (1999). Genetic algorithms : concepts and designs. 1951- Date: London ;New York :Springer,c1999.
  10. Nomura, H., Hayashi, I., and Wakami, N. (8-12 March 1992). A learning method of fuzzy inference rules by descent method. Fuzzy Systems, 1992., IEEE International Conference on, pages 203 - 210.
  11. Rappaport, T. (1996). Wireless communications Principles and practice,3rd Ed. Prentice Hall publication, New Jersey.
  12. Sheu, S. and Wu, C. (2000). Using grey prediction theory to reduce handoff overhead in cellular communication systems. Personal, Indoor and Mobile Radio Communications, 2000. PIMRC 2000. The 11th IEEE International Symposium on, 2(6):782 786.
  13. Shi, Y. and Mizumoto, M. (Aug. 1999). A learning algorithm for tuning fuzzy inference rules. Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE 7899. 1999 IEEE International, 1:378 - 382.
  14. Su, W., Lee, S. J., and Gerla, M. (2000). Mobility prediction in wireless networks. In MILCOM 2000, 21st Century Military Communications Conference Proceedings, volume 1, pages 491-495.
  15. Tran, H. and Harris, R. (2003). Solving qos multicast routing with genetic algorithms. In Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on, volume 3, pages 1944-1948 vol.3.
  16. Tripathi, N., Reed, J., and VanLandinoham, H. (Dec.1998). Handoff in cellular systems. IEEE Personal Communications, 5(6):26-37.
  17. Venkatachalaiah, S., Harris, R., and Murphy, J. (2004). Improving handoff in wireless networks using grey and particle swarm optimisation. In CCCT, volume 5, pages 368-373.
  18. Wu, J.-R. and Ouhyoung, M. (1995). A 3d tracking experiment on latency and its compensation methods in virtual environments. In Proceedings of the 8th annual ACM symposium on User interface and software technology, pages 41-49. ACM Press.
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Paper Citation


in Harvard Style

Venkatachalaiah S. and Harris R. (2005). OPTIMISATION OF HANDOFF PERFORMANCE IN WIRELESS NETWORKS USING EVOLUTIONARY ALGORITHMS . In Proceedings of the Second International Conference on e-Business and Telecommunication Networks - Volume 2: ICETE, ISBN 972-8865-33-3, pages 112-118. DOI: 10.5220/0001413401120118


in Bibtex Style

@conference{icete05,
author={Suresh Venkatachalaiah and Richard J. Harris},
title={OPTIMISATION OF HANDOFF PERFORMANCE IN WIRELESS NETWORKS USING EVOLUTIONARY ALGORITHMS},
booktitle={Proceedings of the Second International Conference on e-Business and Telecommunication Networks - Volume 2: ICETE,},
year={2005},
pages={112-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001413401120118},
isbn={972-8865-33-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on e-Business and Telecommunication Networks - Volume 2: ICETE,
TI - OPTIMISATION OF HANDOFF PERFORMANCE IN WIRELESS NETWORKS USING EVOLUTIONARY ALGORITHMS
SN - 972-8865-33-3
AU - Venkatachalaiah S.
AU - Harris R.
PY - 2005
SP - 112
EP - 118
DO - 10.5220/0001413401120118