By Piotr Gaj, Andrzej Kwiecień, Piotr Stera

This ebook constitutes the completely refereed court cases of the 22st foreign convention on desktop Networks, CN 2015, held in Brunów, Poland, in June 2015. The forty two revised complete papers awarded have been conscientiously reviewed and chosen from seventy nine submissions. The papers in those lawsuits hide the subsequent subject matters: machine networks, dispensed computers, communications and teleinformatics.

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Extra info for Computer Networks: 22nd International Conference, CN 2015, Brunów, Poland, June 16-19, 2015. Proceedings

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CN 2015, CCIS 522, pp. 33–42, 2015. 1007/978-3-319-19419-6 4 34 M. Bernas and B. Placzek a WSN an energy efficient localization method was proposed. Simulations were performed using information collected by sensor nodes from a real-world indoor environment. Various classification methods were analyzed to find the classifier, which gives the best accuracy of the object localization. The rest of this paper is organized as follows: Sect. 2 describes state-of-the-art solutions. Section 3 presents the WSN implementation, data collection algorithm and the classifiers used to find the location of a device.

11 wireless technology (Wi-Fi) became a standard technology that is providing Internet wireless services. The Wi-Fi signal strength, from multiple sources, can also be used to estimate the position of Wi-Fi enabled devices like computers, mobile phones or robots. The utilization of this localization technique can be found in many applications, such as advertisement in malls or medical information system in hospitals. The standard Wi-Fi enabled devices cannot measure direction of the signal, therefore only value of RSSI signal is used in this research to provide a universal solution.

Optimizing data collection for object tracking in wireless sensor networks. , Stera, P. ) CN 2013. CCIS, vol. 370, pp. 485–494. com Abstract. The usage of GPS systems for indoor localization is limited, therefore multiple indirect localization techniques were proposed over the years. 11) access point (AP) signal strength (RSSI) measurement. In this method, a RSSI map is constructed via Localization Fingerprinting (LF), which allows localizing object on the basis of a pattern similarity. The drawback of LF method is the need to create the RSSI map that is used as a training dataset.

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