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- GRASP and grid computing to solve the location area problemPublication . Almeida da Luz, Sónia Maria; Rodriguez-Hermoso, Manuel M.; Vega-Rodriguez, Miguel A.; Gomez-Pulido, Juan A.; Sanchez-Perez, Juan M.In this paper we present a new approach based on the GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic to solve the Location Area (LA) problem over a grid computing environment. All the experiments carried out to complete this study were executed in a real grid environment provided by a virtual organization of the European project EGEE. These experiments were divided into sequential and parallel executions with the intention of analyzing the behavior of the different variants of GRASP when applied to the LA problem. We have used four distinct test networks and also decided to compare the results obtained by this new approach with those achieved through other algorithms from our previous work and also by other authors. The experimental results show that this GRASP based approach is very encouraging because, with the grid computing, the execution time is much more reduced and the results obtained are very similar to those of other techniques proposed in the literature.
- Solving a Realistic Location Area Problem Using SUMATRA Networks with the Scatter Search AlgorithmPublication . Luz, Sónia Maria Almeida da; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.This paper presents a new approach based on the Scatter Search (SS) algorithm applied to the Location Management problem using the Location Area (LA) scheme. The LA scheme is used to achieve the best configuration of the network partitioning, into groups of cells (location areas), that minimizes the costs involved. In this work we execute five distinct experiments with the aim of setting the best values for the Scatter Search parameters, using test networks generated with realistic data [1]. We also want to compare the results obtained by this new approach with those achieved through classical strategies, other algorithms from our previous work and also by other authors. The simulation results show that this SS based approach is very encouraging.
- Applying Scatter Search to the Location Areas ProblemPublication . Luz, Sónia Maria Almeida da; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.The Location Areas scheme is one of the most common strategies to solve the location management problem, which corresponds to the management of the mobile network configuration with the objective of minimizing the involved costs. This paper presents a new approach that uses a Scatter Search based algorithm applied to the Location Areas scheme as a cost optimization problem. With this work we pretend to analyze and set the main parameters of scatter search, using four distinct test networks and compare our results with those achieved by other authors. This is a new approach to this problem and the results obtained are very encouraging because they show that the proposed technique outperforms the existing methods in the literature.
- Differential evolution for solving the mobile location managementPublication . Almeida da Luz, Sónia Maria; Vega-Rodríguez, Miguel A.; Gómez-Púlido, Juan A.; Sánchez-Pérez, Juan M.In this work we present two new approaches to solve the location management problem, respectively, based on the location areas and the reporting cells strategies. The location management problem corresponds to the management of the network configuration with the objective of minimizing the costs involved. We use the differential evolution algorithm to find the best configuration for the location areas and the reporting cells strategies, which principally considers the location update and paging costs. With this work we want to define the best values to the differential evolution configuration, using test networks and also realistic networks, as well as compare our results with the ones obtained by other authors. These two new approaches applied to this problem have given us very good results, when compared with those obtained by other authors.
- Solving the reporting cells problem by using a parallel team of evolutionary algorithmsPublication . D. L. Gonzalez-Alvarez; A. Rubio-Largo; M. A. Vega-Rodriguez; Almeida-Luz, Sónia M.; J. A. Gomez-Pulido; J. M. Sanchez-PerezIn this work, we present a new approach to solve the location management problem by using the reporting cells strategy. Location management is a very important and complex problem in mobile computing which aims to minimize the costs involved. In the reporting cells location management scheme, some cells in the network are designated as reporting cells (RCs). The choice of these cells is not trivial because they affect directly to the cost of the mobile network. This article is focused on the use of high performance computing to execute a parallel heuristic that places optimally the RCs in a mobile network, minimizing its total cost. The main goal of this work is to demonstrate that the collaborative work of different evolutionary algorithms can obtain very good results. For this reason, we have implemented a parallel heuristic and six evolutionary algorithms that works in a parallel way on a cluster to solve the RCs problem.