Based On The Node Density Of Wireless Sensor Network Node Location Technology Research Areas

As one of the most influential technology in the21st century, Wireless Sensor network (WSN) was widespread applicated in many fields e.g., environment monitoring, military security, transportation. Localization is a fundamental issue in wireless sensor networks, for many applications, the network self-localization of sensor nodes can provide the basic information, and has been an important and critical research field in the study of WSN. Based on whether accurate ranging is required, there are basically two types of methods: range-based localization and range-free localization. The former could achieve good accuracy but costly for requiring either per-node ranging hardware or careful system calibration. The later localize nodes based on simple sensing, such as wireless connectivity. With its simple positioning calculation and broad application, DV-Hop became a typical representative of range-free localization and received the most attention.Our work is motivated by the need of accurate location information in heritage protection, a large-scale, non-uniform node and signal distribution sensor network. Driven by the network anisotropic characteristics, we put up a node density-based localization system in earthen site protection, proposed a new technique to improve the localization performance of existing DV-Hop localization algorithm, made it better adjust to the variety of network topology, and improved the practicality of the algorithm in real-life scenarios. The contributions of this work are summarized as follows:1. Anisotropic wireless sensor network modelingThe existing sensor network articles, mostly mentioned such a word "anisotropy", pertaining to a network connectivity differently in each direction, but for the anisotropic degree, no paper have detailed instructions. So, start from the following two aspects:node distribution and signal distribution, we use the number of neighbors and received signal strength indication (RSSI) as the network topology parameters to build an anisotropic WSN model based on the analysis of network anisotropic. This chapter also laid a well foundation for realizing the node density-based sub-regional localization algorithm and also the algorithm performance evaluation.2. Node density-based sub-regional localization technology in anisotropic WSNOn the basis of the study above, we took the positioning accuracy into consideration, improved the traditional DV-Hop algorithm under the condition of irregular network deployment and uneven node distribution, reduced the positioning error caused by the fixed one hop size of DV-Hop. Through region partition, we put up a network node density model as the standard of division, calculated the one hop size separately in different regions. In this way, this approach controlled the error according to the size of the region, so as to improve the precision of node localization.