Solving the Location Areas problem with Strength Pareto Evolutionary Algorithm

In the last few years, the management systems which control the mobile location are becoming more important due to the increase in the number of mobile users. From among the location management techniques, the use of Location Areas is an important strategy which defines the location management task as an optimization problem with two conflicting costs that must be minimized: subscriber location update and paging. In this work, we resort to a multi-objective evolutionary algorithm, Strength Pareto Evolutionary Algorithm 2 (SPEA2), to obtain quasi-optimal solutions of this optimization problem. Furthermore, we compare our results with those obtained by mono-objective algorithms of other authors because, at present, there is not any previous work that tackles the problem with a multi-objective approach. Results show the advantages of solving the Location Areas scheme by using a multi-objective approach.

[1]  Albert Y. Zomaya,et al.  A genetic algorithm for finding optimal location area configurations for mobility management , 2005, The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l.

[2]  Michael E. Theologou,et al.  Computationally efficient algorithms for location area planning in future cellular systems , 2000, Comput. Commun..

[3]  Albert Y. Zomaya,et al.  A simulated annealing approach for mobile location management , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[4]  Albert Y. Zomaya,et al.  The use of a Hopfield neural network in solving the mobility management problem , 2004, The IEEE/ACS International Conference onPervasive Services, 2004. ICPS 2004. Proceedings..

[5]  P.R.L. Gondim,et al.  Genetic algorithms and the location area partitioning problem in cellular networks , 1996, Proceedings of Vehicular Technology Conference - VTC.

[6]  Lothar Thiele,et al.  An evolutionary algorithm for multiobjective optimization: the strength Pareto approach , 1998 .

[7]  Albert Y. Zomaya,et al.  A Combined Genetic-neural Algorithm for Mobility Management , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[8]  Marco Laumanns,et al.  SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization , 2002 .

[9]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[10]  Miguel A. Vega-Rodríguez,et al.  Differential evolution for solving the mobile location management , 2011, Appl. Soft Comput..