Abstract
This paper presents Binary Genetic Algorithm (BGA) is a heuristic, adaptive population based method and which has shown to be a very powerful global search method used for optimization process. Using BGA the objective of this work is used to minimize the location management cost thereby achieve trade-off between location update and paging cost based on reporting cell planning configuration. This BGA algorithm is used to solve location management cost using reporting cell planning problem. With the use of reporting cell location management some cells are designated as reporting cells where mobile station (MS) updates its location upon entering the same coverage. The effectiveness of the technique is tested for collected real data for validation and presented in the paper. The simulation results obtained from this work with reasonable degree of accuracy are very encouraging.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Wong, V., Leung, V.: Location management for next generation personal communication networks. IEEE Network 14(5), 18–24 (2000)
Zhang, J.: Location Management in Cellular networks. In: Handbook of Wireless networks and Mobile Computing, pp. 27–49
Demestichas, P., Georgantas, N., Tzifa, E., Demesticha, V., Striki, M., Kilanioti, M., Theologou, M.: Computationally efficient algorithms for location area planning in future cellular systems. Computer Communications 23(13), 1263–1280 (2000)
Almeida-Luz, S., Vega-Rodriguez, M.A., Gomez-Pulido, J.A., Sanchez-Perez, J.M.: Applying Differential Evolution to the Reporting Cells Problem. In: Proceedings of the International Multiconference on Computer Science and Information Technology, pp. 65–71 (2008)
Sidhu, B., Singh, H.: Location management in cellular networks. In: Proc. of World Academy of Science, Engineering and Technology, vol. 21, pp. 314–319 (2007)
Subrata, R., Zomaya, A.: Artificial Life Techniques for Reporting Cell Planning in Mobile Computing. In: Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS 2002), pp. 169–187 (2003)
Lin, Y.-B., Chlamatac, I.: Wireless and Mobile Network Architecture. John Wiley and Sons, Inc. (2001)
Agrawal, D.P., Zeng, Q.-A.: Introduction to Wireless and Mobile Systems. Thomson Brooks/Cole Inc. (2003)
Al-Tawil, K., Akrami, A., Youssef, H.: A new authentication protocol for GSM networks. In: Proceedings of the 23rd Annual Conference on Local Computer Networks, LCN 1998, October 11-14, pp. 21–30 (1998)
Jie, L., Kameda, H., Keqin, L.: Optimal dynamic location update for PCS networks. In: Proceedings of the 19th IEEE International Conference on Distributed Computing Systems (1998)
Vroblefski, M., Brown, E.C.: A grouping genetic algorithm for registration area planning. Omega 34(3), 220–230 (2006)
Gondim, P.R.: Genetic algorithms and the location area partitioning problem in cellular networks. In: Proc. of Vehicular Technology Conference, pp. 1835–1838 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Parija, S.R., Addanki, P., Sahu, P.K., Singh, S.S. (2015). Cost Reduction in Reporting Cell Planning Configuration Using Soft Computing Algorithm. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_93
Download citation
DOI: https://doi.org/10.1007/978-3-319-11933-5_93
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11932-8
Online ISBN: 978-3-319-11933-5
eBook Packages: EngineeringEngineering (R0)