| Summary: | 碩士 === 中原大學 === 資訊管理研究所 === 97 === Generally speaking, in the dangerous areas such as volcanic areas, frequent earthquake ones, and the vast number of uninhabited ones but they are needed timely monitoring. In such regions which are usually requested some manpower that would have a lot of cost and risks. In order to reduce such cost, we used wireless sensors to monitor and observe. And the methods which contact the sensor with wireless communication, called the wireless sensor network. Due to the development of scientific and technological in the recently years, the size of the sensors are smaller and easier to set up. Therefore, the researches on the wireless sensor network are more and more.
In their studies, the electricity planning is a very important research project due to the configuration of wireless sensor network is regional non-easily accessible areas. Therefore, the power management will have played an important role. Moreover, the power consumption of wireless sensor is generally according to the information transmission and receiver. In such reason, how effective planning of a wireless sensor power consumption rate is our focus in this study.
In this study, we introduce the path planning approach with an average consumption of the overall wireless sensor network in which the power of each node and combine the Dijkstra's algorithm and MTGA algorithm. To result a sets of path planning model that could achieve effective management of wireless sensor network power consumption among nodes. And the experiment will be used Taguchi design experiments. Through the analysis of such experiments, we expect to find the best set of parameters and better results data in order to reduce the power of a large number of depletion of the situation efficiently. In the experiment, this study used mathematical methods that can make the power depletion control effectively which reach maximize survival time goals, and find an effective path planning model that let users could transfer some information by such a path planning mode.
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