Abstract
This manuscript addresses a vital task in any Public Land Mobile Network, the mobile location management. This management task is tackled following the Reporting Cells strategy. Basically, the Reporting Cells planning consists in selecting a subset of network cells as Reporting Cells with the aim of controlling the subscribers’ movement and minimizing the signaling traffic. In previous works, the Reporting Cells Planning Problem was optimized by using single-objective metaheuristics, in which the two objective functions were linearly combined. This technique simplifies the optimization problem but has got several drawbacks. In this work, with the aim of avoiding such drawbacks, we have adapted a well-known multiobjective metaheuristic: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Furthermore, a multiobjective approach obtains a wide range of solutions (each one related to a specific trade-off between objectives), and hence, it gives the possibility of selecting the solution that best adjusts to the real state of the signaling network. The quality of our proposal is checked by means of an experimental study, where we demonstrate that our version of NSGAII outperforms other algorithms published in the literature.
This is a preview of subscription content, log in via an institution to check access.
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
Agrawal, D., Zeng, Q.: Introduction to Wireless and Mobile Systems. Cengage Learning (2010)
Mukherjee, A., Bandyopadhyay, S., Saha, D.: Location Management and Routing in Mobile Wireless Networks. Artech House mobile communications series. Artech House (2003)
Taheri, J., Zomaya, A.Y.: A combined genetic-neural algorithm for mobility management. J. Math. Model. Algorithms, 481–507 (2007)
Bar-Noy, A., Kessler, I.: Tracking mobile users in wireless communications networks. IEEE Transactions on Information Theory 39(6), 1877–1886 (1993)
Boukerche, A.: Handbook of Algorithms for Wireless Networking and Mobile Computing. Chapman & Hall/CRC Computer & Information Science Series. Taylor & Francis (2005)
Subrata, R., Zomaya, A.Y.: A comparison of three artificial life techniques for Reporting Cell planning in mobile computing. IEEE Trans. Parallel Distrib. Syst. 14(2), 142–153 (2003)
Alba, E., García-Nieto, J., Taheri, J., Zomaya, A.Y.: New Research in Nature Inspired Algorithms for Mobility Management in GSM Networks. In: Giacobini, M., et al. (eds.) EvoWorkshops 2008. LNCS, vol. 4974, pp. 1–10. Springer, Heidelberg (2008)
Almeida-Luz, S.M., Vega-Rodríguez, M.A., Gómez-Pulido, J.A., Sánchez-Pérez, J.M.: Applying differential evolution to the Reporting Cells problem. In: International Multiconference on Computer Science and Information Technology, pp. 65–71 (2008)
Almeida-Luz, S.M., Vega-Rodríguez, M.A., Gómez-Pulido, J.A., Sánchez-Pérez, J.M.: Solving the Reporting Cells Problem Using a Scatter Search Based Algorithm. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS, vol. 6086, pp. 534–543. Springer, Heidelberg (2010)
Hac, A., Zhou, X.: Locating strategies for Personal Communication Networks: A novel tracking strategy. IEEE Journal on Selected Areas in Communications 15(8), 1425–1436 (1997)
Coello, C.A.C., Lamont, G.B., Veldhuizen, D.A.V.: Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation). Springer-Verlag New York Inc., Secaucus (2006)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6(2), 182–197 (2002)
ILOG Inc: ILOG CPLEX: High-performance software for mathematical programming and optimization (2006). http://www.ilog.com/products/cplex/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Berrocal-Plaza, V., Vega-Rodríguez, M.A., Sánchez-Pérez, J.M. (2014). Studying the Reporting Cells Planning with the Non-dominated Sorting Genetic Algorithm II. In: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-662-45523-4_6
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45522-7
Online ISBN: 978-3-662-45523-4
eBook Packages: Computer ScienceComputer Science (R0)