项目名称: 基于数据融合的大规模无线传感器网络的时空覆盖研究
项目编号: No.61202350
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 计算机科学学科
项目作者: 常相茂
作者单位: 南京航空航天大学
项目金额: 25万元
中文摘要: 无线传感器网络(WSN)是目前非常活跃的一个领域,具有广阔的应用前景。覆盖问题是WSN中的一个基本问题,是在资源有限的情况下,对WSN各种资源进行有效分配的研究。高性能要求与资源有限的矛盾要求WSN中的节点必须进行合作,然而现有工作大都基于简单的感知模型而无法实现节点的有效合作。数据融合可实现多传感器的合作感知,然而大部分现有的数据融合方案都集中在为小规模网络设计最优的融合算法上,无法在大规模WSN中应用。本项目将研究大规模WSN中基于数据融合的覆盖方案,通过完善感知模型、设计适合移动节点的融合方案且优化移动规则、设计同时优化感知和通信的能量管理方案,使大规模WSN的覆盖性能较现有结果有较大提升。在理论方面,本项目将分析WSN中各种参量之间的相互关系,使得设计者可在系统配置前对各个参量进行准确的预算;在应用方面,本项目将建立数据融合与大规模WSN设计间的桥梁,由此设计出性能更好的覆盖方案。
中文关键词: SINR-PRR模型;链路质量;水上碎片检测;决策融合感知;UAV辅助网络
英文摘要: Wireless Sensor Networks (WSNs) is a very active field with numerous important applications. Sensing coverage is a fundamental problem in WSN which ensures sensing quality of a network under the limited resources. The conflict between high performance requirements and the limited resources requires the efficient collaboration among sensors in WSN. However, most of the existing work based on simplistic sensing models cannot facilitate efficient sensor collaboration. Data fusion is a well-established signal processing technique to process data from multiple sensors. However, most of existing data fusion studies focus on the optimization of fusion algorithms for a small number of sensors,and cannot be applied to large-scale WSNs. This project plans to study novel coverage schemes for large-scale WSNs based on data fusion. Compared with the existing work, this project aims to significantly improve the coverage performance through realistic sensing models, design novel fusion schemes and movement scheduling algorithms for mobile sensors, and design power management schemes to improve both sensing and communication performance. From a scientific aspect, this project will develop advanced performance models that allow network designer to analyze and predict the sensing performance of large-scale WSNs. From a practical
英文关键词: SINR-PRR model;link performance;quatic debris monitoring;fusion decision sensing;UAV aided network