This paper describes the deployment optimization technology and the cross-layer design of a surveil- lance WSN system applied in relic protection.Facing the typical technical challenges in the application context of relic protection,we firstly propose a deployment technology based on ant colony optimization al- gorithm(DT-ACO)to overcome the difficulties in communication connectivity and sensing coverage. Meanwhile,DT-ACO minimizes the overall cost of the system as much as possible.Secondly we propose a novel power-aware cross-layer scheme(PACS)to facilitate adjustable system lifetime and surveillance accuracy.The performance analysis shows that we achieve lower device cost,significant extension of the system lifetime and improvement on the data delivery rate compared with the traditional methods.

This paper introduced some typical data aggregation algorithms firstly.Then based on a tree topology and a kind of sleeping schedule scheme,built an energy model of sensor node.Finally,evaluated the performance of data aggregation on energy by simulation.

Data aggregation is an important research area in Wireless Sensor Networks(WSN).In WSN,using data aggregation technique can bring the following benefits:saving energy,improving data gathering efficiency,enhancing data accuracy,getting integrated information and so on.Time series analysis is a statistical method which is used to reveal dynamic architecture and changing rule of certain system according to dynamic data.In this paper,a forecast-based temporal data aggregation technique is proposed based on time series model and time series forecast method.The effect and performance of the method is verified and evaluated by simulation using the temperature data collected by an environment monitoring network deployed in Forbidden City.The results show that autoregressive(AR) algorithm is more effective than others for WSN.When error threshold is 0.05 ℃ to 0.50 ℃,forecast success ratio is 21% to 83%.When error threshold is 0.05 ℃,energy saving is up to 68%.

环境监测网络是无线传感器网络的一项典型实际应用.无线传感器网络环境监测技术在监测规模、监测地域、监测准确度和监测灵活程度等方面都有传统监控手段难以比拟的优势.