A multiobjective study of the Gaussian cluster paging in the Reporting Cells strategy ?
Mobile location management is an important task in mobile networks. This paper presents an analysis of the Gaussian cluster paging in the Reporting Cells strategy. Reporting Cells define a location update strategy in which some network cells are configured as Reporting Cells with the aim of tracking the subscribers movement. On the other hand, the Gaussian cluster paging is a paging scheme where we assume that the probability of finding a callee's terminal decreases as we move away from the last updated location. This paging scheme is studied in a multiobjective way for different probability thresholds, and considering time-delay constraints. With the goal of finding the best possible sets of non-dominated solutions, we propose our implementation of a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II. By means of an experimental study, we show that each probability threshold has its own non-dominated region in the objective space.
mobile location management non-dominated sorting genetic algorithm ii reporting cells scheme gaussian paging multiobjective evolutionary optimization