Optimizing the mobility management task in networks of four world capital cities
In this paper, we study one of the most important management tasks in any Public Land Mobile Network: the mobile location management. In this management task, the network cells are grouped into logical areas (called the Registration Areas) in order to avoid the overload of the signaling network. The proper dimensioning of these Registration Areas is an important engineering issue that is modeled as a bi-objective optimization problem. In previous works by other authors, the Registration Areas planning problem was optimized by using the linear aggregation of the objective functions. This technique allows simplifying the optimization problem but has several drawbacks. That is why, we use our versions of two multiobjective optimization algorithms. Furthermore, a multiobjective approach provides a wide range of solutions among which the network operator could select the one that best meets its real requirements. With the aim of studying the mobile location management in realistic mobile environments, we have generated four novel mobile activity traces by importing four real networks topologies into a mobile networks simulation tool. Experimental results show that our proposals are very interesting because they achieve better solutions than the single-objective optimization algorithms proposed by other authors in a very less execution time.
mobile location management registration areas planning multiobjective evolutionary optimization