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Using multi-objective metaheuristics for the optimal selection of positioning systems

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Abstract

The interworking between cellular and wireless local area networks, as well as the spreading of mobile devices equipped with several positioning technologies pave the ground to new and more favorable indoor/outdoor location-based services (LBSs). Thus, wireless internet service providers are required to take several positioning methods into account at the same time, to leverage the different features of existing technologies. This would allow providing LBSs satisfying the user-required quality of position in terms of accuracy, privacy, power consumption, and often, conflicting features. Therefore, this paper presents GlobalPreLoc, a multi-objective strategy for the dynamic and optimal selection of positioning technologies. The strategy exploits a pattern-mining algorithm for future position prediction combined with conventional multi-objective evolutionary algorithms, for choosing continuously the best location providers, accounting for the user requirements, the terminal capabilities, and the surrounding positioning infrastructures. To practically implement the strategy, we also designed an architecture based on secure user plane location specification to provide indoor and outdoor LBSs in interworking wireless networks exploiting GlobalPreLoc features.

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Notes

  1. An area, as defined in Sect. 3.2, groups adjacent zones covered by the same positioning technology; the movement to a new area occurs whenever a SET enters an area covered by a positioning technology different from the current one.

  2. Note that, the zones predicted at each future timestamp are not necessarily different from each other.

  3. jMetal is freely available at http://jmetal.sourceforge.net/.

  4. p Values are adjusted by the Bonferroni correction to account for multiple comparison protection.

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Authors and Affiliations

  1. Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università degli Studi di Napoli, Via Roma 29, 81031, Aversa, Italy

    Massimo Ficco

  2. Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125, Naples, Italy

    Roberto Pietrantuono & Stefano Russo

Authors
  1. Massimo Ficco
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  2. Roberto Pietrantuono
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  3. Stefano Russo
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Correspondence to Massimo Ficco.

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Communicated by V. Loia.

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Ficco, M., Pietrantuono, R. & Russo, S. Using multi-objective metaheuristics for the optimal selection of positioning systems. Soft Comput 20, 2641–2664 (2016). https://doi.org/10.1007/s00500-015-1665-x

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  • DOI: https://doi.org/10.1007/s00500-015-1665-x

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