面向環(huán)境監(jiān)測(cè)的無(wú)線傳感網(wǎng)絡(luò)的功耗管理研究.pdf

1、Wireless sensor networks (WSNs) are composed of thousands of sensor nodes by self-organizing multi-hop routing. The energy of wireless sensor node is generally provided by the battery. However，once the battery of the nod

2、e runs out，the node has to withdraw from the WSNS.Therefore，power consumption has become one of the main issues for the design of WSNs.Against the power consumption of nodes，this thesis discussed the background，the chara

3、cteristics of WSNs，dynamic power management (DPM) of sensor nodes，information fusion related research，and carried out a thorough analysis of single node sturcture and the energy consumption of each part of the node. Agai

4、nst the application preventing forest fire of the WSNs，the DPM strategy and information fusion technology are used to reduce the power consumption of the node. It is verification against the practice application shows th

5、at the proposed method can reduce the power consumption of the node greatly. The thesis mainly includes the following three parts:1、The method of improved index average prediction is proposed through an analysis of the s

6、hortage of the existing index average model，the proposed method obtains significant improvement in terms of adaptive and accuracy. Using the improved exponential model to forecast the future free time，and determining whe

7、ther the node should be converted to a low power mode by comparing predicting results with transition threshold of the actual nodeS.The proposed prediction Strategy of DPM can implement adaptively adjustment quickly duri

8、ng emergency，which can reduce the power consumption of WSNs by improving the accuracy of prediction.2、According to the analysis of the practical application environment，the characteristic value can be obtained at the ear

9、ly stage of frost fire. Under the condition of the stable environment，the existing grey model methods can get accurate result. But under the circumstance of the environment rapid change，significant error will be made bas

10、ed on this model.. Against this，a modified grey model is proposed to predict the future environment parameters，and comparing with the working state of the node is determined by comparing with the eigenvalue. Finally powe

11、r reduction of the nodes is achieved.3、The ambient temperature and relative humidity collected by a single node are analyzed in information fusion. Through this，the amount of data transmission of nodes is reduced，which f