臺灣博碩士論文加值系統

在無線感測網路 (Wireless sensor networks)中電池能量的消耗決定了感測器可以工作的時間，因此控制能量的消耗在無線感測的研究上是一個重要的議題。在此論文中，我們提出了一個分散式傳輸能量的控制的演算法，此演算法不只是延長了感測器工作的時間，也維持了傳輸封包的成功率，除此以外也可以降低傳輸時封包碰撞的機率，在設計演算法之前，我們做了許多的實驗來發現在不同的傳送能量上影響封包成功率的因素來設計演算法。在演算法中感測器使用訊號強度指標(Received Signal Strength Indicator)與連結品質指標(Link Quality Indicator) 來決定對於鄰居感測器的傳送能量。演算法中的參數皆由實驗的結果來得出最佳的設定，由於環境是隨著時間的變化，以至於固定的傳送能量無法去適應環境的變化，因此在演算法中感應器可以動態的根據環境的變化來調整傳送封包的能量，來達到保證封包的成功率以及減少感測器能量的消耗，在最後實驗的結果顯示分散式能量控制演算法可以依據環境的變化來調整傳送的能量以及保證封包的成功率，在能量的節省上也有不錯的表現。

In wireless sensor networks, senor nodes’ lifetime depend on their battery energy. Thus, the power saving on sensor nodes is a critical issue in wireless sensor networks. In this paper, we proposed a distributed adaptive transmission power control algorithm which cannot only prolong the lifetime of sensor nodes by saving the energy consumption but enhance the performance of packet delivery ratio. Besides, it can also reduce the interference between transmitting nodes. Before designing our algorithm, we firstly investigated the impact of link quality when utilizing different transmission power by analyzing lots of experimental data, and then design our algorithm based on those experimental results. In our algorithm, each node utilizes the RSSI (Received Signal Strength Indicator) value and LQI (Link Quality Indicator) value of the radio to determine the appropriate transmission power for its neighbors. Our algorithm can dynamically adjust the transmission power with the environment change. All of our experiments are implemented on the MICAz platform. The experimental results show that our algorithm can save power energy and guarantee a good link quality for each pair of communications.

Chapter 1 Introduction 1
Chapter 2 Related Works 4
Chapter 3 Distributed Adaptive Transmission
Power Control Algorithm 9
3.1 Initial Phase 10
3.2 Maintaining Phase 14
Chapter 4 Experimental Results 28
Chapter 5 Conclusions 31
References 32

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