Abstract
In this work, we propose a parallel version of our adaptation of the Non-dominated Sorting Genetic Algorithm II (NSGAII) with the aim of reducing its execution time when solving the Registration Areas Planning Problem (RAPP), a problem that describes one of the most popular strategies to manage the subscribers’ movement in a mobile communication network. In this problem, the use of mobile activity traces is a good choice that allows us to assess the Registration Areas strategy in an accurate way. However and due to the huge number of mobile subscribers, a mobile activity trace of a current network could contain several millions of events, which leads to a large execution time. That is the reason why we propose to parallelize our version of NSGAII in a shared memory system, using for that the OpenMP Application Program Interface. The quality and efficiency of our approach is shown by means of an experimental study.
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GSM Association (GSMA): The Mobile Economy (2013).
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Acknowledgments
This work was partially funded by the Spanish Ministry of Economy and Competitiveness and the ERDF (European Regional Development Fund), under the contract TIN2012-30685 (BIO project). The work of Víctor Berrocal-Plaza has been developed under the Grant FPU-AP2010-5841 from the Spanish Government.
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Berrocal-Plaza, V., Vega-Rodríguez, M.A., Sánchez-Pérez, J.M. (2015). Parallelizing NSGAII for Accelerating the Registration Areas Optimization in Mobile Communication Networks. In: Onieva, E., Santos, I., Osaba, E., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2015. Lecture Notes in Computer Science(), vol 9121. Springer, Cham. https://doi.org/10.1007/978-3-319-19644-2_51
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