A modified hopfield network for mobility management
This paper presents a new approach to solving the mobile location management problem using the Paging Cells (PCs) scheme. In this approach (HNN-BDT-PC), a combination of the Hopfield Neural Network (HNN) and the author's Ball Dropping Technique (BDT) is used to solve the problem. To this end, the location management cost of a network is embedded in the HNN parameters, and by iteration, the mobile network gradually moves toward an optimal state. The approach is inspired by the phenomenon that results from the natural movement of balls when they are dropped onto a non-even plate (a plate with troughs and crests). Each trough of the plate corresponds to a PC, and the network corresponds to the whole plate. The aim is to find optimal PC configuration (i.e., the troughs) of the network. Three main procedures are used in the optimization process; in each optimization cycle, the HNN is launched to move the balls around the plate, and, by analogy, to move the PCs around the network to find the best configuration. Copyright (c) 2007 John Wiley & Sons, Ltd.
mobile location management hopfield neural network paging cells scheme