Aplicación de algoritmos evolutivos al problema de gestión de la localización en redes móviles

Abstract

The Location Management (LM) problem corresponds to the characterization of the network configuration with the objective of minimizing the cost involved, mainly those associated to the user movements and respective tracing. The location management is partitioned in two main operations: location update that corresponds to the notification of current location, performed by mobile terminals when they change their location in the mobile network, and location inquiry (paging) that represents the operation of determining the location of the mobile user terminal, performed by the network when it tries to direct an incoming call to the user. Considering the LM problem there exist several strategies divided between static and dynamic schemes, but our focus were the Location Area (LA) and the Reporting Cell (RC) problems, two of the most common static ones in actual mobile networks, because both consider, for all the users, the same network behavior. The core work of this thesis was the investigation and application of Evolutionary Algorithms (EA) to both of the problems, including the analysis and comparison of results achieved using test networks, generated with pattern simulation, and also realistic networks, based on real data extraction. Taking in consideration the experiments performed, the results achieved and the respective comparison with those accomplished by using other artificial life techniques published in the literature, we noticed that our results are very competitive, mainly those obtained by our SS (Scatter Search) based approaches, when applied to the LA and the RC problems.