在無線感測器網路(Wireless Sensor Networks, WSNs)環境裡提升網路的生命週期(Lifetime)一直是個重要的探討議題；尤其感測器節點在被隨機分佈後，會因資訊的傳輸(Transmission)或接收(Receiver)等功能不斷的執行，而漸漸的消耗節點有限能源(Energy)，如此導致無線感測器網路的功效受到影響，甚至造成網路運作的癱瘓。因此，研究如何使感測器節點能源有效運用為重要的議題；如此，才能延伸無線感測器網路的生命週期，使節點於偵測蒐集資訊後，可以有效的傳輸到資料收集中心(Base Station)，並藉由偵測及蒐集後資訊進行資料的分析，便於了解周遭環境的異動變化，而可以達到事先防患的工作。
論文中針對感測器節點有限能源問題之運用有進一步的研究，將採動態方式使節點能有效率的控制能源 (Power Control)並以休眠排程(Sleep Scheduling)為基礎，提出一個可以有效率的動態傳輸能源控制(Dynamic Transmit Power Control)之演算法，使節點能即時調整power level值，以減少不必要的傳輸能源浪費，同時，論文中使用休眠排程為基礎，透過休眠排程分配方法，當節點不需要擔任資料傳輸工作時，可以讓節點進入休眠狀態，以減少節點的閒置聆聽時間 (Reduce Idle Listen)，以降低資料被大量的傳送（Overhead），而造成資料碰撞(Collision)等問題，如此可以有效的延伸無線感測器網路之生命周期。
所以，論文中提出一個應用於無線感測器網路中以休眠排程為基礎之電源管控機制演算法，於此演算法下可以簡單即時的調整節點間的能源控制及休眠排程；如此，節點可以得到有效的能源控制與管理，更可以使節點在無線感測網路中得以發揮特殊的偵測功效。
依據論文中所提出的演算法，我們將進行整合性模擬實驗，並將此實驗的數據值與相關議題做分析比較。模擬實驗將可以有效的提昇在無線網路中節點的傳輸資料之平均能源消耗(Average Energy Consumption)及整體網路架構之生命週期的延伸也將會有較為明顯的改善。

The prolonging of sensor network lifetime is a very important research area at present. This is due to the fact that when sensor nodes are deployed randomly, the frequent transmission of sensed data packets between these nodes depletes node residual energy, which effectively shortens the overall network lifespan. Thus, there is a need to improve the energy efficiency of sensor node operation in order to prolong sensor network lifetimes. Furthermore, if sensor operations can be performed more efficiently, data would be collected more reliably and effectively by sensors and relayed to the base station, facilitating the detection of changes in the sensed environment.
In this dissertation, we focus on the problem of energy conservation in sensor networks. We propose a novel power control mechanism based on sleep scheduling to dynamically control the transmission power of sensors and reduce the number of data transmissions required. This mechanism efficiently schedules nodes to sleep when sensor data transmissions are not required. Consequently, this reduces the amount of idle listening, in-network data transmissions and other network issues such as packet collision, This prolongs the lifetime of the network.
Sleep scheduling is the basis for the algorithm used within the power control mechanism for the wireless sensor network. The algorithm enables a node's transmission power to be effectively controlled/managed and as a result, the node's sensing operations can be maximized. Based on the algorithm, experimental trials are then performed and the results thus obtained are compared to the results from existing methods. The results obtained show that a sensor node’s average energy consumption for data transmission is improved through our approach.

Contents
中文摘要                                                  Ⅰ
Abstract                                                  Ⅲ
Contents                                                  Ⅴ
List of Figures                                           Ⅷ
List of Tables                                            Ⅹ
1.Introduction                                             1
1.1  Background ．．．．．．．．．．．．．．．．．．．． ．5
1.2  Motivation  ．．．．．．．．．．．．．．．．．．．．．7
1.3  Goals ．．．．．．．．．．．．．．．．．．．．．．．．9
2.Theoretical Background                                  12
2.1  Transmission Power Control techniques(TPC) ．．．．．14
2.2  Adaptive Transmission Power Control (ATPC) ．．．．．17
2.3  Transmission Power Control and Blacklisting(PCBL)  ．20
2.4  Randomly Sleep period ．．．．．．．．．．．．．．． 23
2.5  Fixed Sleep Period ．．．．．．．．．．．．．．．．．24
2.5.1  Sensor Mac (S-Mac) ．．．．．．．．．．．．．．．．24
2.5.2  Timeout Mac (T-Mac) ．．．．．．．．．．．．．．． 27
3.Power Control based on Sleep Scheduling                 28
3.1  Transmission Power Control (TPC) ．．．．．．．．．．28
3.2  Power Control based on Sleep Scheduling ．．．．．． 30
3.2.1  Create Tables ．．．．．．．．．．．．．．．．．． 32
3.2.2  Sleep Scheduling ．．．．．．．．．．．．．．．．．36
3.2.3  Transmit Packets and Adjust TPC ．．．．．．．．． 41
4.Experimental Evaluation                                 43
4.1  Experimental environment ．．．．．．．．．．．．．．45
4.1.1  Routing Protocol ．．．．．．．．．．．．．．．．．46
4.2  Experimental result and analysis comparison  ．．．．50
4.2.1  Average Remain Energy base on Random ．．．．．．．50
4.2.2  Average Remain Energy base on Sleep Scheduling．． 52
4.2.3  Active Nodes base on Sleep Scheduling ．．．．．． 54
4.2.4  Packet Reception Rate base on Sleep Scheduling ．．56
5.Conclusions and Future works                            58
5.1  Conclusions  ．．．．．．．．．．．．．．．．．．．．58
5.2  Future works  ．．．．．．．．．．．．．．．．．．． 60
Bibliography                                              61
Appendix A. Publication List                              65
Appendix B. 	   	                              66
Appendix C.		                              75

List of Figures
Figure 1-1.Block diagram for the H/W of sensor node ．． ．3
Figure 2-1.Routing by CLUSTERPOW in a typical non-homogeneous network ．．．．．．．．．．．．．．．．．．．15
Figure 2-2. Feedback Closed Loop Overview for ATPC ．．． 17
Figure 2-3. Transmission Power vs. RSSI ．．．．．．．．．19
Figure 2-4. Randomly Sleep Period ．．．．．．．．．．．．23
Figure 2-5. Fixed Sleep Period ．．．．．．．．．．．．． 24
Figure 2-6. S-MAC Packet information change diagram ．．．25
Figure 2-7. T-MAC Sleep Period Timing ．．．．．．．．．．27
Figure 3-1. Transmission Power Control ．．．．．．．．． 29
Figure 3-2. Transmission Power Control based on Sleep Scheduling Flow Chart   ．．．．．．．．．．．．．．．．．31
Figure 3-3. First stage initialization flow chart ．．．．32
Figure 3-4. Mica2 device’s power level, energy consumption and range ．．．．．．．．．．．．．．．．．．．．．．．  35
Figure 3-5. Sleep Scheduling Algorithm ．．．．．．．．． 37
Figure 3-6. Interrupt point Time (Tirq) usage example ．．39
Figure 3-7. Transmit Packets and Adjust TPC  ．． ．．．．42
Figure 4-1. Delphi program to analyze and MS-SQL database 46
Figure 4-2. Routing Protocol  ．．．．．．．．．．．．．．47
Figure 4-3. Setup Layer  ．．．．．．．．．．．．．．． ．49
Figure 4-4. TPC average remain energy comparison ．． ．．51
Figure 4-5. TPC & TPC base on Sleep Scheduling average remain energy ．．．．．．．．．．．．．．．．．．．．．．53
Figure 4-6. Node survive ratio in each record ．．．．．．55
Figure 4-7. Packet Reception Rate ．．．．．．．．．．．．57

List of Tables
Table 3-1. Owner Information Table (OIT) ．．．． ．．．．34
Table 3-2. Neighbor Information Table (NIT) ．．．．．．．35
Table 3-3. Mica2 Power Table (MPT) ．．．．．．．．． ．．35
Table 4-1. Setup Layer Table (SLT) ．．．．．．．．．．． 48

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