近年來，無線感測網路（wireless sensor networks, WSNs）議題已經引起許多注意。這樣的網路環境可以由很多廉價的節點組成，每個節點都能收集、儲存，以及處理環境訊息，並且透過無線連結方式與基地台聯繫。在本論文中，我們研究一個在無線感測網路中十分重要的議題，能量損耗的問題，這問題反映出一個感測區域的部署方式。因此，無線感測網路的應用有密切關鍵的是網路的壽命問題。此外，無線感測網路的基本特性，『覆蓋性』可以反映出感測網路如何藉由感測器節點來監督與定位追蹤。因此，我們將此問題闡述為一種決策性問題，並設計出在感測區域中每一個服務點都可以至少被K個不同感測器節點服務。K為給定的參數。本文中應用遺傳基因演算法（GA）有效率節省能源的方式來解決部署無線感測網路時監督與目標定位服務的問題。

Recently, wireless sensor networks have attracted a lot of attention. Such environments may consist of many inexpensive nodes, each capable of collecting, storing, and processing environmental information, and communicating with base station nodes through wireless links. In this paper, we survey a fundamental problem in wireless sensor networks, the energy consumption problem, which reflects how well a sensor field is deployed. Therefore, a critical aspect of applications with wireless sensor networks is network lifetime. Furthermore, one of the fundamental issues in sensor networks is the coverage problem, which reflects how well a sensor network is monitored or tracked by sensors. We formulate this problem as a decision problem, whose goal is to determine whether every point in the service area of the sensor network is covered by at least k sensors, where k is a given parameter. In this paper, we propose an energy-efficient method based on Genetic Algorithms to deal with the deployment problem of wireless sensor networks such that it provides target-location and surveillance services.

摘要........................................................................i
Abstract..................................................................ii
目錄......................................................................iii
圖表目錄...............................................................v

第一章 研究動機與簡介.....................................1
1.1 無線感測網路.................................................1
1.2 研究動機.........................................................2
1.3 章節介紹.........................................................3

第二章 相關文獻探討.........................................4
2.1 無線感測網路議題.........................................4
2.2 無線感測網路設計問題..................................7

第三章 我們的方法............................................15
3.1 設計問題公式化描述....................................15
3.2 遺傳基因演算法............................................17
3.3 GA運算流程.................................................20
3.4 應用GA設計無線感測網路.........................21
3.5 Tabu Search改進方式...................................24

第四章 實驗結果與分析....................................26
4.1 模擬環境........................................................26
4.2 實驗結果........................................................26

第五章 結論........................................................30

參考文獻................................................................31

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