Matching State Estimation Scheme for Content-Based Sensor Search in the Web of Things

More recently, an increasing number of object-attached sensors are publishing their real-time state on the Internet by using state-of-the-art Web technologies, which make the sensor search service extremely important for the Web of Things (WoT). However, the existing issues that the sensor search service is facing bring huge challenges to the design of matching state estimation scheme. In this paper, an architecture of high-efficiency content-based sensor search system is depicted to provide a prototype system for sensor search. And then a matching state estimation scheme is proposed in detail, including a sensor state prediction approach to accurately estimate future sensor readings and a match estimating and verifying approach to effectively classify and verify candidate sensors, in order to enhance the performance of our search system. Simulation results show that our matching state estimation scheme dramatically reduces the communication overhead of search system and achieves excellent performance in terms of recall ratio and precision ratio