Improving node localization in WSN by using obstruction level indicator

Abstract

Wireless sensor networks can be used in habitat monitoring for detecting fire, in disaster for helping rescue teams and in agriculture for sensing humidity. Node localization is essential for some important sensor network applications. Despite the high relative accuracy of some localization algorithms, node localization is still an opened research area, due to the physical phenomena such as attenuation, reflection, diffraction, scattering and so forth. The current developed algorithms have different accuracy when are tested under dissimilar environments. We propose to use Smart Beacon Nodes (SBNs) to infer the Obstruction Level Indicator over an occupied area, then, use this indicator for estimating the distance among nodes. In our experimental simulation, SBNs decrease the node localization error of Triangular Centroid Localization and Weighted Centroid Localization up to 18%.

Smart Environmental Architecture for Node Localization in a Wireless Sensor Network

“…But, if the environment condition changes, the distance estimation accuracy also changes. In [15] is presented the Smart Beacon Nodes, which are able to estimate the Obstacle Level Indicators (OLI) among beacon nodes, i.e., the number of obstacles per square meter in the coverage range of each beacon node. The indicator is expedient for those NLAs based on distance, particularly when density of obstacles changes frequently.…”

“…However, most range-based NLAs are not able to use The OLI Matrix directly by themselves. In (ii), The distance Matrix among beacon nodes and non-beacon nodes is estimated such as it is done in [15] by using The OLI Matrix. In (iii) the range-based NLAs employ The distance matrix for estimating the non-beacon node position.…”

“…The Figure 1 depicts our architecture, which is made up of five elements: (i) The SBNs [15], (ii) the distance estimation process, (iii) NLAs, (iv) the LPN [16], and (iv) the evaluator. In (i), the SBNs are able to provide two kinds of OLIs among them.…”

“…In this paper, we propose the Smart Environmental Architecture for Node Localization (SEA-NL), which includes the three key factors identified. Our architecture is made up of two main elements: (i) the Smart Beacon Nodes [15] and (ii) the Logical Position of Nodes [16]. In (i) beacon nodes are able to estimate the obstacle level among them.…”