Research On Device-free Localization And Its Data Reliable Transmission In Wireless Sensor Networks

Wireless sensor networks (WSNs) have received intensive research interests in recent years with the rapid development of the Internet of things and the wireless communication technology. Since WSNs can effectively sense, measure and collect the monitoring information, they are widely used in environment monitoring, health monitoring, and target localization and tracking. Among these applications, localization is the fundamental for many applications, such as activity monitoring and real-time tracking, thus it has received widely attention of researchers. Therefore, it is of great significance to study the localization in WSNs, which will have a far-reaching impact on human life.Device-Free Localization (DFL) without attaching any device to the target, thus it has attracted intensive research interests. Although there are many achievements in today's DFL, the existing methods still face the following challenges in real-world applications:Firstly, the existing DFL methods depend on dense deployment and high cost of human labor to achieve the high accuracy, thus, these methods are not cost-effective and scalable, especially in large scale monitoring area. Secondly, although the existing methods can achieve a high localization accuracy, they ignore the pervasive and robustness of the system. Thirdly, the localization deployment structures are always complex in real-world, i.e., the strip structure. Due to the complex strip structure, the existing data transmission in DFL will suffer low reliability, high energy consumption, and high delay, which will resulte in a low localization accuracy. Therefore, it is of great practical significance to study the pervasive and low-cost DFL.Our goal is to achieve a low cost, high accuracy and high reliable DFL system based on two technologies:localization and its data transmission. The main contributions of this paper are as follows:Firstly, in this paper, we propose the RSS fingerprint-based localization technique using Grid division and CLassification (GCL), which can achieve high localization accuracy without dense deployment. In essence, GCL leverages the RSS and the diffraction theory to enable RSS-based DFL in sensor networks. Specifically, we analyze the fine-grained RSS distribution properties at a variety of node distances and reveal that the structure of the triangle is efficient for low-cost DFL. Finally, we use Bayes' theorem, fuzzy logic and neural networks to establish the location model based on the fine-grained RSS fingerprint. Experimental results show that GCL can improve the localization accuracy compared to the existing approaches.Secondly, we propose a novel model based DFL system named "FindIt" to significantly reduce the labor cost and improve the robustness of the existing DFL. Taking diffraction, reflection and penetration loss caused by the target into consideration, FindIt successfully correlates the target location with the RSS readings of a wireless link without any offline training. We then propose a Weighted Voting Algorithm (WVA) to assign different weights to different links based on the amount of RSS fluctuations to remove noise and enhance localization accuracy in rich multipath environment. We implement FindIt on cheap COTS devices and extensive experiments demonstrate the effectiveness of FindIt. FindIt can achieve a high accuracy without any offline training, outperforming the stateof-the-art schemes.Thirdly, we propose a lightweight geographic opportunistic routing approach to cope with the routing problem in the complex strip structure for DFL system. To do so, we propose the Virtual Plane Mirror (VPM) algorithm to select forwarding candidate, which is inspired by the light propagation. In addition, two implementation problems of VPM, transmission spread angle and the communication range, are thoroughly analyzed based on the percolation theory. Experimental results show that the successful transmission rate of VPM is higher than the state-of-the-art approaches.Finally, we propose a reliable transmission control strategy named "LIPS" (Light Propagation Selection) to solve the poor reliability, high energy consumption and large delay problems in localization system. To do so, we assign priorities to each forwarding candidate based on its distance to the sink node and its residual energy, then we choose the candidate which has the highest priority as the preferred forwarder. To avoid packet loss, LIPS exploits a virtual plane mirror to make turning points of complex strip structure seem to disappear. Furthermore, we use the transmission angle to determine the range of candidate set. Finally, we prove that the length of the transmission path generated by VPM is at most two times the length of the shortest path. Experimental results show that the successful transmission rate of LIPS is higher than the state-of-the-art approaches, meanwhile LIPS has a lower communication overhead and energy consumption rate.