Research On Data Publishing Technology And Localization Technology Of Sensor Network

With the development of sensor technology and enhancement of sensor capability, sensor network applications have been pervasive and becoming more and more scalable in many fields, including military, environment surveillance, medical care, and other human's daily lives, etc. In addition, conceptions of Smart Earth and Internet of Things (IOT) indicate that the sensor network applications will be available in each corner of human's lives.With such scalable sensor network deployed, it is one important issue that how we should reasonably publish and share sensor data. In the paper, we firstly study the sensor network data publishing technology, simply introduce Sensor Web and its corresponding frameworks, and depict the Mesh-up technology, Google Maps framework and Microsoft SensorMap architecture. Then based on the OceanSense project which's one of our team's fruits, we design and realize a framework used for publishing ocean sensor network data (OsnWeb). With the help of Google Maps APIs and Web Services, OsnWeb successfully publishes wireless sensor network and surveillance data of OceanSense based on Google Maps.What's more, in order to exactly localize sensor nodes of OceanSense, the paper does some research on sensor network localization technology, extends PI location algorithm published by our team and proposes extended PI rotation location algorithm which localizes one sensor by geometric relationship between sensor node and beacon node. Compared with TRL and BI location algorithm, the precision of PI rotation location algorithm is increased by 68% and 57% respectively.Major contributions of this paper are as follows:1) Based on Web Services, Mesh-up technology and Google Maps APIs, the paper designs and implements a framework used for publishing and visualizing surveillance data of OceanSense deployed by our team.2) The paper extends PI location algorithm which is one of our team's fruits, proposes the extended PI rotation algorithm. Compared with TRL and BI location methods, the precision of PI rotation location algorithm is increased by 68% and 57% respectively.