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研究生:施嘉興
研究生(外文):Jia-ShingShih
論文名稱:無線感測網路省能管理機制與方法
論文名稱(外文):Power Consumption Adjustment and Management Mechanism in Wireless Sensor Networks
指導教授:鄭憲宗鄭憲宗引用關係
指導教授(外文):Sheng-Tzong Cheng
學位類別:博士
校院名稱:國立成功大學
系所名稱:資訊工程學系碩博士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:英文
論文頁數:76
中文關鍵詞:無線感測網路功率調整傳輸功率干擾實體層MAC 層網宇實體系統基因演算法
外文關鍵詞:wireless sensor networkpower adjustmenttransmission powerinterferencephysical layerMAC layercyber physical systemactuator controlgenetic algorithmfuzzy decision makinglifetime
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在過去幾年以來,無線感測網路相關的應用與科技都有長足的進步。相關學
者的研究也完整地將一些感測技術的標準(如:IEEE 802.15.4[1] 與 Zigbee)
實際應用到各項的領域中,如:家庭安全、健康照護、軍事或數位生活…等等。
未來也將會有更多以無線感測網路為基礎的應用。
本篇論文我們將探套有關於無線感測領域中能源消耗的相關議題與解決方
法。首先我們將會先著重在無線感測網路本身的實體層與MAC 層。我們提出MLPA的方法,並透過數理分析的模型來將傳輸的功率能源切割成m 個階層(m-LPA)。
由數學分析來看,透過計算設定出適當的傳輸功率在最理想的狀況下將只需要原
本固定傳輸功率的三分之一能源。除此之外更可以延長2.5 倍使用時間。我們也
整理出本方法m 階層與密度之前的模擬結果。並且本方法可以實際運用在無線感
測器上且不需要考慮GPS 定位、感測器間距與干擾問題。
探討完無線感測器本身的能源消耗改善方法後,我們發現在無線感測網路中
會有網洞(Holes)的問題。在佈建無線感測網路時,有時因為地形環境或是隨機
佈置無線感測器的關係,而產生在路徑上無法聯繫的區塊空間即為網洞。網洞形
成將會使網路資訊傳遞造成癱瘓。因此大多的研究者會透過路由路徑的規劃與方
法,想辦法讓封包自行繞過該網洞,使得資訊可以順利傳遞。但這些方法通常會
快速耗損網洞周圍的無線感測器能源,並且使得網洞的空間變得更大。因此本篇
論文在第二個階段便提出一個方法,透過能源導向多路徑傳輸規劃來繞過網洞。
我們的方法不僅僅是將封包透過最短的路徑來繞過網洞,並且會考量網洞周圍無
線感測器的負載程度來繞徑。透過模擬的結果,我們提出的方法可以有效地透過
低能源耗損方式並考量網路負載平衡的狀況下來將封包繞過網洞傳遞到目的地。
在我們透過m-LPA 與多路徑的方法來解決無線感測網路中的能源消耗問題
後,最後我們將目光移轉到透過無線感測網路在省能上的應用。近年來,全球都
相當關注於能源議題,不管是創造新能源或是節省現有能源都十分重要。能源供
給的問題一直以來都是我們面對的重要議題。在目前替代能源非常有限的情況
下,透過一個良好合理的省能策略來節省能源將是我們努力的目標。本篇論文在
最後我們藉由網宇實體系統提出一個以基因演算法為基底的方法規劃與操控電
力。我們的方法不僅僅是排班執行,更考量實際環境變數來加以修正。我們提出
可以藉由一群相同功能但有不同能力的電子產品,加上一群散佈在空間中的無線
感測器感測電子產品的實際影響,再有另一群感測器收集環境變數來進行預測。
透過本篇論文的方法與上述三種設備的交互運用來達到省能的目的。從模擬結果
中可以看出我們所提出的GAAC 方法應用在網宇實體系統中的確可以在我們預設
的功能目標點內有效地降低能源耗損,達到省能的目的。
In the past few years, there has been much improvement in the technology and the application of WSNs. Researchers have compiled complete sets of standards for real cases (e.g., IEEE 802.15.4[1] and Zigbee) spanning a wide range of applications including home security, private-sector organizations, health care, and the military.
There is more and more applications base on wireless sensor networks. In this thesis, we talk about power consumption issue and methods in wireless sensor network. First, we focus on physical layer and MAC layer. We constructed an
analytical model of the MLPA mechanism with m distinct power levels (m-LPA). For m-LPA, the closed-form expression of the optimal power setting was determined and the mean transmission power was minimized to one third of the original fixed transmission power. Thus, each node can extend the lifetime by 2.5 times. We have shown the relations between m and density in simulation results. Although the mechanism worked smoothly in our study, the sensors don’t need to handle the distance and interference problem.
After first part, we find holes problem in wireless sensor networks often causes traditional routing algorithms to fail. Most of the previous research on the subject addressed the routing-hole problem by using static detour paths to route data packets along the boundaries of holes. In these scenarios, the energy of sensor nodes on static paths depletes quickly, and the hole size enlarges. In this thesis, we propose a scheme for bypassing holes in wireless sensor networks by exploiting energy-aware multiple paths. Our approach not only takes into account shorter paths for bypassing holes, but also eases the loading of the sensor nodes on the boundaries of holes. Simulation results show that the proposed scheme can achieve short detour paths, low energy consumption, and network load balancing.
At last, after we are using m-LPA and multi-path mechanisms to solve power consumption problem in wireless sensor network. We start to focus on energy saving application based on wireless sensor network. In recent years, the public has been paying ever greater attention to problems associated with energy production and consumption. Energy-supply issues rightly constitute one of the most important issues that we face. In the absence of any viable alternative energy supply, a strategy that would result in energy savings is a legitimate goal. In this thesis, we propose a genetic algorithm-based method by which electrical operators in a cyber physical system could be scheduled and controlled. Our method accounts for not only process output
but also environmental variation. We propose that the electrical operators be of the same function but with different capabilities. One set of sensors would be placed
dispersedly around the to-be-affected area for measuring the output of the processes.
Another set of sensors would collect the environmental variation value for prediction purposes. The simulation results show that the application of our proposed GA-based
Actuator Control (GAAC) method to the aforementioned cyber physical system can minimize its power consumption while accomplishing the desired set point.
摘要…………………………………………………………………………… I
Abstract………………………………………………………………………… III
誌謝…………………………………………………………………………… V
List of Tables……………………………………………………………………VIII
List of Figures………………………………………………………………… IX
Chapter 1.Introduction………………………………………………………… 1
Chapter 2.Related Work……………………………………………………… 7
2.1 Related work of MLPA………………………………………………… 7
2.2 Related work of bypass hole problem…………………………………… 9
2.3 Related work of cyber physical system………………………………… 11
Chapter 3.MLPA……………………………………………………………… 14
3.1 Multi-level Power-adjustment Mechanism……………………………… 16
3.2 Optimal Multi-level Power-configuration Analysis……………………… 18
Chapter 4.Multi-Path Construction………………………………………… 26
4.1 System Model…………………………………………………………… 26
4.2 Hole Shape Modeling…………………………………………………… 27
4.3 Multi-Path Construction………………………………………………… 31
4.4 Bypassing Path Selection………………………………………………… 36
Chapter 5.GAAC SYSTEM MODEL AND THE GAAC METHOD……… 38
5.1 Cyber Physical System Model…………………………………………… 38
5.2 Parameter Definitions…………………………………………………… 41
5.3 Weighted Least Squares Error…………………………………………… 42
5.4 Central Control Module………………………………………………… 43
5.5 Binary-coded Genetic Algorithm……………………………………… 44
Chapter 6.Simulation………………………………………………………… 47
6.1 Performance Analysis and Results of MLPA…………………………… 47
6.2 Performance Evaluation of Multi-Path Construction…………………… 53
6.3 Simulation of GAAC…………………………………………………… 59
Chapter 7.Concluction……………………………………………………… 65
Reference……………………………………………………………………… 68
VITA…………………………………………………………………………… 74
Publication List……………………………………………………………… 75
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