Movlab – Laboratory of Technologies for Interactions and Interfaces

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http://hdl.handle.net/10437/11004

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Percorrer Movlab – Laboratory of Technologies for Interactions and Interfaces por assunto "ALGORITMOS"

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    Algorithms for Estimating the Location of Remote Nodes Using Smartphones
    (IEEE, 2019) Pedro, Dario; Tomic, Slavisa; Bernardo, Luís; Beko, Marko; Oliveira, Rodolfo; Dinis, Rui; Pinto, Paulo; Amaral, Pedro; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    Locating the position of a remote node on a wireless network is becoming more relevant, as we move forward in the Internet of things and in autonomous vehicles. This paper proposes a new system to implement the location of remote nodes. A new prototype Android application has been developed to collect real measurements and to study the performance of several smartphone's sensors and location algorithms, including an innovative one, based on the second order cone programming (SOCP) relaxation. The application collects theWiFi access points information and the terminal location. An internal odometry module developed for the prototype is used when Android's service is unavailable. This paper compares the performance of existing location estimators given in closed form, an existing SOCP one, and the new SOCP location estimator proposed, which has reduced complexity. An algorithm to merge measurements from non-identical terminals is also proposed. Cooperative and terminal stand-alone operations are compared, showing a higher performance for SOCP-based ones, that are capable of estimating the path loss exponent and the transmission power. The heterogeneous terminals were also used in the tests. Our results show that the accurate positioning of static remote entities can be achieved using a single smartphone. On the other hand, the accurate real-time positioning of the mobile terminal is provided when three or more scattered terminal nodes cooperate sharing the samples taken synchronously.
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    Elephant Herding Optimization for Energy-Based Localization
    (MDPI, 2018) Correia, Sérgio; Beko, Marko; Cruz, Luís Alberto da Silva; Tomic, Slavisa; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations, we approach it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics are applied to this type of problem. More specifically, an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as a performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.