摘要
We present a novel paradigm of sensor placement concerning data precision and estimation.Multiple abstract sensors are used to measure a quantity of a moving target in the scenario of a wireless sensor network.These sensors can cooperate with each other to obtain a precise estimate of the quantity in a real-time manner.We consider a problem on planning a minimum-cost scheme of sensor placement with desired data precision and resource consumption.Measured data is modeled as a Gaussian random variable with a changeable variance.A gird model is used to approximate the problem.We solve the problem with a heuristic algorithm using branch-and-bound method and tabu search.Our experiments demonstrate that the algorithm is correct in a certain tolerance,and it is also efficient and scalable.
We present a novel paradigm of sensor placement concerning data precision and estimation. Multiple abstract sensors are used to measure a quantity of a moving target in the scenario of a wireless sensor network. These sensors can cooperate with each other to obtain a precise estimate of the quantity in a real-time manner. We consider a problem on planning a minimum-cost scheme of sensor placement with desired data precision and resource consumption. Measured data is modeled as a Gaussian random variable with a changeable variance. A gird model is used to approximate the problem. We solve the problem with a heuristic algorithm using branch-and-bound method and tabu search. Our experiments demonstrate that the algorithm is correct in a certain tolerance, and it is also efficient and scalable.
出处
《系统仿真技术》
2008年第2期98-101,共4页
System Simulation Technology
基金
Supported of Project of Fok Ying Tong Education Foundation(No.104030)
Supported of Key Project of National Natural Science of Foundation of China(No.70531020)
Supported of Project of New Century Excellent Talent(No.NCET-06-0382)
Supported of Key Project of Education Ministry of China(No.306023)
Supported of Project of Doctoral Education(20070247075)
关键词
传感器
无线技术
网络
数据处理
terms-sensor placement
data fusion
optimization
heuristic algorithm
wireless sensor networks
