Studying the Reporting Cells strategy in a realistic mobile environment

Abstract

In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting Cells. In this location management strategy, a mobile station only updates its location when moving to a new Reporting Cell, and it is free to move among non-Reporting Cells without updating its location. The Reporting Cells Planning Problem can be classified as a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the number of paging messages. With the aim of finding the best possible set of non-dominated solutions, we have implemented a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Experimental results show that our proposal is able to achieve good sets of non-dominated solutions and, at the same time, to improve the results obtained with other optimization techniques.