臺灣博碩士論文加值系統

無線通訊技術蓬勃的發展，為人類現代生活帶來更多的便利與舒適。在短程無線通訊網路中，藍芽是非常重要的關鍵技術之一，可藉由多組微網連結成分散網路來延伸通訊的距離。藍芽節點在角色扮演中，可分為主節點、從節點及橋接節點。其主節點及橋接節點是造成資料流量之主要瓶頸，因此控制好微網之規模，可以獲得較佳的服務品質以及較低的電力消耗。本篇論文中我們提出兩個新的結構，分別為BlueTree++及BlueTree#，可用來強化分散網路的執行效能；它們是先設定分散網路內之微網為中等規模以下，以減少橋接節點之通訊代價，同時限定每個橋接節點只能扮演slave/slave的角色，以減少橋接節點在角色切換時所帶來的時間及頻寬的損失；另外BlueTree#架構可允許橋接節點可以連接兩組以上之微網，以增加分散網路之靈活性。本論文也回顧討論幾種適用於分散網結構的方法。在我們的研究裡，BlueTree++ 以及 BlueTree#可以提供更有規模大小調整之分散網路拓樸結構，同時分散網路之最長傳輸路徑及其規模大小，都是可以評估的。此外，我們也實作一個平台可作為藍芽通訊的節點。

With the vigorous development of wireless technology, the life style of human being could be improved to get more convenience and comfort. Bluetooth is a critical technology applied in a shorter distance for wireless networks. Furthermore, the roles of Bluetooth devices can be divided into types: master, slave, and bridge. However, knowing that master or bridge nodes are the bottleneck of data traffic flow. Controlling the scale of piconets is required to obtain better QoS and lower power consumption. This study presents two novel formations called BlueTree++ and BlueTree# to enhance the performance of scatternet, using a medium quantity of piconets to decrease large amount of bridge overhead and limiting each bridge could only act a slave/slave role to decrease bandwidth utility during role switching. Moreover, there could be more than two links on each bridge node to avoid “parking” of slaves and associated overhead for applying scatternet more flexible. This paper also reviews existing approaches which are discussed to flexibly apply scatternet. Experimental results indicate that our formations outperform other formations in scalability, performance, and a tree structure maintained. In our studies, BlueTree++ and BlueTree# could provide more scalable topology than BlueTree. The longest routing path and the scale of scatternet also could be evaluated. Furthermore, we had built a platform to implement a Bluetooth node for a basic application.

中文摘要 i
Abstract ii
Table of Contents iii
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Overview of the Research 2
1.3 Thesis Organization 3
Chapter 2 Related Work 4
2.1 Bluetree 7
2.2 BlueNet 8
2.3 BlueStar 9
2.4 BlueRing 11
2.5 Summary 11
Chapter 3 BlueTree++ Family 12
3.1 BlueTree 12
3.2 BlueTree++ Algorithm 15
3.3 BlueTree++ Definition 25
3.4 BlueTree++ Analysis 27
3.5 Special Case Study - BlueRing 30
Chapter 4 BlueTree# Family 32
4.1 BlueTree# Algorithm 32
4.2 BlueTree# Definition 36
4.3 Node Quantity for a Full BlueTree# 37
4.4 Special Case Study 39
Chapter 5 Experimental Results 41
5.1 Expanding Scale of BlueTree 41
5.2 Expanding Scale of BlueTree++ Compared with Bluetree 43
5.3 Expanding Scale of BlueTree# Compared with Bluetree 55
5.4 Summary 66
Chapter 6 Platform Implementation 67
Chapter 7 Conclusions and Future Work 73
References 74

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