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

机译:物联网中基于内容的传感器搜索的匹配状态估计方案

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摘要

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.
机译:最近,越来越多的带有对象的传感器通过使用最新的Web技术在Internet上发布其实时状态,这使传感器搜索服务对于物联网(WoT)极为重要。然而,传感器搜索服务所面临的现有问题给匹配状态估计方案的设计带来了巨大的挑战。在本文中,描述了一种基于内容的高效传感器搜索系统架构,以提供用于传感器搜索的原型系统。然后详细提出了一种匹配状态估计方案,包括一种可以准确估计未来传感器读数的传感器状态预测方法,以及一种可以有效地对候选传感器进行分类和验证的匹配估计和验证方法,以提高我们搜索系统的性能。仿真结果表明,我们的匹配状态估计方案大大降低了搜索系统的通信开销,并且在查全率和查准率方面均具有出色的性能。

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