The Study of Grouping WSN for Different BS Locations

碩士 === 朝陽科技大學 === 資訊與通訊系 === 104 === In recent years, wireless sensor network applications are more and more diverse. But, in front of a variety of applications, they also require to overcome technical, such as limited power. Because the sense node is loaded with a general battery, reducing energy c...

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Bibliographic Details
Main Authors: MING-KAI HSU, 許明凱
Other Authors: JIUN-JIAN LIAW
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/10456698886456697773
Description
Summary:碩士 === 朝陽科技大學 === 資訊與通訊系 === 104 === In recent years, wireless sensor network applications are more and more diverse. But, in front of a variety of applications, they also require to overcome technical, such as limited power. Because the sense node is loaded with a general battery, reducing energy consumption at sensing nodes is an issue of current numerous research. In order to reduce the energy consumption of sensing nodes and increase the survival time of sensor networks. We have a variety of ways to reduce the energy consumption of sense nodes, such as improved hardware or altering data transfer agreements and the like. Contents of this paper mainly want to find a data transfer protocol to reduce the energy consumption of sensing nodes. So this study is based on MSGCH method to improve methods of energy distribution groups by taking advantage of the relationship between a number of groups and a base station distance. When the group is farther away from the base station, it can get more energy. Therefore, the far away group has more energy to transmit data, whose concept can be based to increase the survival time of sensor networks. In the simulation, this research carries four different types of study, which combines BS (Base Station) located within or outside the sensing areas, and the homogeneous or heterogeneous sensor network. The final results show that as long as the BS is located outside the sensing area, either homogeneous or heterogeneous sensor networks have better results; however, when the BS is located inside the sensing area, homogeneous sensor networks have not good results, but heterogeneous sensor networks have in-between results. In summary, although results are either good or bad, the poor results are not particularly bad; therefore, we believe that our approach is feasible.