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Wyświetlanie 1-3 z 3
Tytuł:
Multiobjective Approach to Localization in Wireless Sensor Networks
Autorzy:
Marks, M.
Niewiadomska-Szynkiewicz, E.
Powiązania:
https://bibliotekanauki.pl/articles/309060.pdf
Data publikacji:
2009
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
ad hoc networks
localization
simulated annealing
stochastic optimization
wireless sensor network
Opis:
Wireless sensor network localization is a complex problem that can be solved using different types of methods and algorithms. Nowadays, it is a popular research topic. What becomes obvious is that there are several criteria which are essential when we consider wireless sensor networks. Our objective is to determine accurate estimates of nodes location under the constraints for hardware cost, energy consumption and computation capabilities. In this paper the application of stochastic optimization for performing localization of nodes is discussed. We describe two phase scheme that uses a combination of the trilateration method, along with the simulated annealing optimization algorithm. We investigate two variants of our technique, i.e., centralized and distributed. The attention is paid to the convergence of our algorithm for different network topologies and trade-off between its efficiency and localization accuracy.
Źródło:
Journal of Telecommunications and Information Technology; 2009, 3; 59-67
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Localization in Wireless Sensor Networks Using Heuristic Optimization Techniques
Autorzy:
Niewiadomska-Szynkiewicz, E.
Marks, M.
Kamola, M.
Powiązania:
https://bibliotekanauki.pl/articles/308429.pdf
Data publikacji:
2011
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
evolutionary strategy
genetic algorithm
localization
location systems
nonconvex optimization
simulated annealing
wireless sensor network
Opis:
Many applications of wireless sensor networks (WSN) require information about the geographic location of each sensor node. Devices that form WSN are expected to be remotely deployed in large numbers in a sensing field, and to self-organize to perform sensing and acting task. The goal of localization is to assign geographic coordinates to each device with unknown position in the deployment area. Recently, the popular strategy is to apply optimization algorithms to solve the localization problem. In this paper, we address issues associated with the application of heuristic techniques to accurate localization of nodes in a WSN system. We survey and discuss the location systems based on simulated annealing, genetic algorithms and evolutionary strategies. Finally, we describe and evaluate our methods that combine trilateration and heuristic optimization.
Źródło:
Journal of Telecommunications and Information Technology; 2011, 4; 55-64
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization schemes for wireless sensor network localization
Autorzy:
Niewiadomska-Szynkiewicz, E.
Marks, M.
Powiązania:
https://bibliotekanauki.pl/articles/907665.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sieć bezprzewodowa
sieć sensorowa
lokalizacja
optymalizacja stochastyczna
wyżarzanie symulowane
wireless sensor networks
localization
stochastic optimization
simulated annealing
Opis:
Many applications of wireless sensor networks (WSN) require information about the geographical location of each sensor node. Self-organization and localization capabilities are one of the most important requirements in sensor networks. This paper provides an overview of centralized distance-based algorithms for estimating the positions of nodes in a sensor network. We discuss and compare three approaches: semidefinite programming, simulated annealing and two-phase stochastic optimization-a hybrid scheme that we have proposed. We analyze the properties of all listed methods and report the results of numerical tests. Particular attention is paid to our technique-the two-phase method-that uses a combination of trilateration, and stochastic optimization for performing sensor localization. We describe its performance in the case of centralized and distributed implementations.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2009, 19, 2; 291-302
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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