Localização Tolerante a Falhas de Usuários Móveis em Ambientes Fechados
Abstract
The knowledge of a mobile device location is essential for the development of context-aware applications. This paper investigates solutions for the location problem, in indoor environments, that cater for low cost, precision, and fault tolerance requirements. In addition, the feasibility of execution in devices with restricted resources and the processing time required to execute the location function are also of concern. Specifically, we evaluate two solutions using Neural Networks and the k-nearest neighbor’s algorithm, which use radio signals generated by access points to mobile networks. A real physical scenario was used to implement and evaluate the techniques.References
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Brunato, M. e Battiti, R. (2005). Statistical learning theory for location fingerprinting in wireless LANs. Computer Networks, 47(6):825–845.
Gandhi, R. (2003). Tolerance to access-point failures in dependable wireless local-area networks. IEEE Workshop on Object-Oriented Real-Time Dependable Systems, pp. 136–143, Nápoles, Itália.
Ito, S. e Kawaguchi, N. (2005). Bayesian based location estimation system using wireless LAN. IEEE Workshop on Object-Oriented Real-Time Dependable Systems, pp. 273–278, Kauai Island, HI, EUA.
Kontkanen, P., Myllymäki, P., Roos, T., Tirri, H., Valtonen, K., e Wettig, H. (2004). Chap. 11: Probabilistic methods for location estimation in wireless networks. Ganesh, R., Kota, S., Pahlavan, K., e Agustı́, R., editores, Emerging Location Aware Broadband Wireless Adhoc Networks, pp. 173–187. Kluwer Academic Publishers.
Kröse, B. (1996). An introduction to neural networks. Universidade de Amsterdam. http://citeseer.ist.psu.edu/ose96introduction.html.
Prasithsangaree, P., Krishnamurthy, P., e Chrysanthis, P. K. (2002). On indoor position location with wireless LANs. IEEE Symposium on Personal, Indoor, and Mobile Radio Communications, pp. 273–278, Lisboa, Portugal.
Rodriguez, M., Favela, J., Martı́nez, E., e Muñoz, M. (2004). Location-aware access to hospital information and services. IEEE Transactions on Information Technology in Biomedicine, 8(4):448–455.
Universidade de Stuttgart (20 05). Stuttgart neural network simulator. http://www-ra.informatik.uni-tuebingen.de/SNNS/.
Yu, L., Wang, S., e Lai, K. (2006). An integrated data preparation scheme for neural network data analysis. IEEE Transactions on Knowledge and Data Engineering, 18(2):217–230.
Published
2006-05-29
How to Cite
COPETTI, Alessandro; LEITE, J. C. B.; LOQUES, Orlando.
Localização Tolerante a Falhas de Usuários Móveis em Ambientes Fechados. In: FAULT TOLERANCE WORKSHOP (WTF), 7. , 2006, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2006
.
p. 87-98.
ISSN 2595-2684.
DOI: https://doi.org/10.5753/wtf.2006.23354.
