A multiobjective study of the Gaussian cluster paging in the Reporting Cells strategy

作者：Berrocal Plaza Victor^*; Vega Rodriguez Miguel A; Sanchez Perez Juan M

来源：Applied Soft Computing, 2015, 28: 332-344.

DOI：10.1016/j.asoc.2014.12.005

• Mobile location management
• Reporting Cells scheme
• Gaussian paging
• Multiobjective evolutionary optimization
• Non-dominated Sorting Genetic Algorithm II

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.

• 出版日期2015-3