LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN
Ad Hoc NetworksPublished 9 December 2011Open access
Diego F. Larios, Julio Barbancho, Francisco Javier Molina, Carlos León
Citations38
SJR quartileQ1
SJR score1.21
SNIP1.45
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TL;DR
A novel tracking distributed method for localization of the sensor nodes using moving devices in a network of static nodes, which have no additional hardware requirements is proposed and it is demonstrated that the proposed method obtains less localization errors and better accuracy than the centroid algorithm.
Abstract
The localization of the sensor nodes is a fundamental problem in wireless sensor networks.\n\t\t\t\t There are a lot of different kinds of solutions in the literature. Some of them use external\n\t\t\t\t devices like GPS, while others use special hardware or implicit parameters in wireless\n\t\t\t\t communications.\n\t\t\t\t In applications like wildlife localization in a natural environment, where the power available\n\t\t\t\t and the weight are big restrictions, the use of hungry energy devices like GPS or hardware\n\t\t\t\t that add extra weight like mobile directional antenna is not a good solution.\n\t\t\t\t Due to these reasons it would be better to use the localization’s implicit characteristics in\n\t\t\t\t communications, such as connectivity, number of hops or RSSI. The measurement related\n\t\t\t\t to these parameters are currently integrated in most radio devices. These measurement\n\t\t\t\t techniques are based on the beacons’ transmissions between the devices.\n\t\t\t\t In the current study, a novel tracking distributed method, called LIS, for localization of\n\t\t\t\t the sensor nodes using moving devices in a network of static nodes, which have no additional\n\t\t\t\t hardware requirements is proposed.\n\t\t\t\t The position is obtained with the combination of two algorithms; one based on a local\n\t\t\t\t node using a fuzzy system to obtain a partial solution and the other based on a centralized\n\t\t\t\t method which merges all the partial solutions. The centralized algorithm is based on the\n\t\t\t\t calculation of the centroid of the partial solutions.\n\t\t\t\t Advantages of using fuzzy system versus the classical Centroid Localization (CL)\n\t\t\t\t algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for\n\t\t\t\t testing localization algorithms.\n\t\t\t\t With this simulator, it is demonstrated that the proposed method obtains less localization\n\t\t\t\t errors and better accuracy than the centroid algorithm.
Keywords
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