臺灣博碩士論文加值系統

最近幾年來，由於無線網路設備的大幅進展，以及無線網路所帶來的便利性，讓無線網路在世界各地已經成為一種風潮，不論是筆記型電腦、個人數位助理等等易於隨身攜帶的電子產品，都已內建有無線上網的裝備，也因此讓世界各地都興起了一股新的浪潮，不論在校園還是各種公共場合，大部分都會在其管轄的範圍內，建有一些無線網路的基地台，無論學生或是顧客都能夠隨時上網，也因此可知道現在世界上無線網路的重要性。
但是無線網路還是有一些比不上有線網路的地方，就如同無線網路最重要的兩項特點：一、較少的頻寬，二、能量的限制，也因為這兩項特性，讓無線網路的應用有了一些限制，因此很多人都針對這兩樣特性作了一些改善，如讓產能最高以及讓能量的使用有效率等等。
然而，對於有關產能跟能量的改善，大部分所考慮的都是在網路是完美的情況下，也就是考慮封包在傳輸時不會有發生遺失的情況，但是在實際的網路上，無線網路會因為一些情況，如障礙物遮敝等等，因而發生封包遺失的情況，也因為會發生封包遺失的情況，因此對於傳輸時的封包，我們必須作一些調整，例如封包長度、加上偵測錯誤的標頭等等，而在此論文中，我們是針對封包長度去作調整。
在此篇論文中，我們考慮在無線網路上去作封包長度的調整，網路傳送封包時，其產能(throughput)以及所消秏的能量跟封包長度有關，當考慮位元錯誤率(bit error rate, BER)與封包錯誤率(packet error rate, PER)時，便可以由過去錯誤率的統計以及網路的狀況來適時改變封包長度，針對不同的網路狀態找到最適合的封包長度，使產能能夠增加，並且讓能量的使用更有效率，也因此讓網路的頻寬及能量沒有大量的秏費在遺失的封包上。
在此論文中，我們是以群聚型無線感測網路(clustering-based WSN)當作所提出方法的應用，其原因是無線感測網路具有複雜的無線通訊網路拓樸，傳輸型態多元化，傳輸型態包含節點之間的通訊、節點至近端閘道(cluster head)、閘道之間、閘道至遠端基地台、以及節點至基地台之通訊等等類型。除此之外，為了呈現所提出方法在移動式無線網路也具有良好的適用性，我們並發展了雜訊錯誤率之等效距離模型，根據網路雜訊現狀來換算等效距離，並藉此等效距離重組無線感測網路拓樸組態並進行能量比例式封包繞送(Energy Proportional Routing, EPR)，這樣的模型網路等效於節點之間的距離乃是隨時間變動，亦即等效於節點之移動，這也突破無線感測網路節點必須是固定位置的限制，而無線感測網路在現今文獻上鮮少封包長度調節以及距離變化之探討。
在此論文中，我們會先利用所求得的數學式去推導最佳化的封包長度，然後以NS2去模擬所推得的最佳化的封包長度，並列出模擬結果。我們以數個實驗模擬模型和所數學分析的結果互相驗證，其中數據包含base station所接收到的總資料量、產能、以及能量使用率，並依據這些數據作一些檢討，並和現今無線感測網路其它相關的文獻作進行比較，證明我們所導出來的公式正確性以及所提出模型的優越性。

Due to amazing technology progress of wireless networks facilities in recent years, wireless networks become popular and popular in the world. Many products, such as notebooks and personal digital assistants, have built-in wireless networking devices. This makes the world raise a new trend. Many places have base stations for wireless accesses. Researches in the field of wireless networks become more and more important.
Though wireless networks provide much convenience, in some aspects they are worse than wired networks, such as two of the most important drawbacks -- limited bandwidth and limited energy. These drawbacks limit applications of wireless networks. Therefore, many people make some improvements in increasing throughputs and energy utilizations. However, most of these improvements are studied assuming data are transferred over the perfect network channels -- no noises in the network channels. However, in real world, wireless networks usually have serious packet loss problem due to high noises and many uncertain and un predictable factors such as the barrier of the buildings. Due to the packet losses in wireless networks, we must adapt the transmitted packets, such as the packets lengths. Therefore, in the thesis, we adapt the packet lengths according to different network conditions.
In this thesis, we consider adjusting packet length in wireless networks. When networks transmit packets, throughput and the dissipated energy are related to packets lengths. When we consider bit error rate (BER) and packet error rate (PER), we adapt the packet lengths according to error statistics and network conditions so that throughput and energy utilization are increased. Therefore, this saves great part of network bandwidth and energy wastes from packet losses.
In this thesis, we use the clustering-based wireless sensor networks (WSNs) as an application of the proposed method. The reason using WSNs as exemplar is that the WSNs usually have complicated network topology comprising a great deal of transmission types. Transmitting types include communications among sensor nodes, from sensor nodes to cluster heads (gateways), among gateways, from gateways to the remote base station, from sensor nodes directly to the base station, and so on. In addition, to present the applicability of the proposed method in mobile wireless networks, we also develop the equivalent distance model of noise error rates. We calculate the equivalent distance according to the network condition. In addition, through the equivalent distance model we reorganize clusters in the wireless sensor network and thus obtain a new topology. Then we perform energy proportional routing (EPR) for each newly formed topology every round. Since the equivalent distances among sensor nodes are time-variant, this implies that the sensor nodes are mobile. In contrast to conventional approaches that seldom discuss adaptation of packet lengths and variation of distances in wireless sensor networks, the proposed mechanism breaks through the restriction that the positions of sensor nodes are fixed.
In this thesis, we derive the optimal packet length formulae from some mathematical equations. Then we use NS2 to simulate the proposed model and list the simulation results. We verify the proposed model by comparing simulation results with mathematics analyses. The simulation results include throughput, energy utilization, and the total data amount received by the base station. From these simulations, we compare with the latest research studies related with wireless sensor networks as to prove that the proposed method is superior and beneficial.

Contents
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Wireless Networks 4
1.2.1 Link-Layer Protocols 4
1.2.2 Media Access Control (MAC) Protocols 5
1.2.3 Model of operation 6
1.3 Organization of The Thesis 8
Chapter 2 Background 9
2.1 Noise Models 9
2.2 Wireless Sensor Networks (WSNs) 13
Chapter 3 Related Works 18
3.1 Radio Energy Model In Wireless Network 18
3.2 Throughput and Energy Utilization 19
3.3 Error Rate Statistics 20
Chapter 4 Effect of Packet Length in Throughput and Energy Utilization 22
4.1 Throughput 24
4.2 Energy Utilization 25
4.3 The Optimal Packet Length 27
4.4 Equivalent Distance 32
Chapter 5 Application in Clustering-Based Wireless Sensor Networks 34
5.1 Routing Protocols In Sensor Networks 34
5.2 State-of-Art Protocols 35
5.2.1 LEACH PROTOCOL 36
5.2.2 PEGASIS 38
5.2.3 Energy Proportional Routing (EPR) 39
5.3 Applying The Proposed Model in Clustering-Based WSN with EPR 45
Chapter 6 Simulations and Analysis 47
6.1 Simulation Scenarios 47
6.2 Experimental Results 49
6.2.1 Constant Bit Error Rate 50
6.2.2 Variable Bit Error Rate 53
6.3 The Evaluation of Packet Adaptation 62
6.4 The Results of Equivalent Distance 63
6.5 Evaluation of Equivalent Distance 67
Chapter 7 Conclusion 71
7.1 Conclusion 71
7.2 Future Work 72
Appendix A NS2 Introduction 74
References 80

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