臺灣博碩士論文加值系統

過去幾年，隨著無線網路技術的進步與蓬勃發展，使得無線網路的架設門檻越來越低。再加上內建無線網卡的筆記型電腦日趨普及，使得使用者對無線網路的需求越來越高。在這種趨勢下，出現了一種高密集的無線網路，亦即是一種由多個無線基地台密集架設所構成的大範圍無線網路。然而，在目前的連結架構下，高密集無線網路中選擇基地台的依據僅賴訊號強度。如此一來，這種方式會因為忽略了基地台目前的承載量，而選擇了一個訊號強度雖然強，但承載量也很高的基地台，因此無法得到好的效能。而且無線網路仍存在干擾問題，也使得無線網路的效能因此而下降；有鑑於此，既有的架構中實做了傳輸速率的調變來獲得效能的提升。

在本篇論文中，我們提出了一個新的可實際運行的連線架構，利用三台無線基地台、四台筆記型電腦、以及一個2.4GHz無線電話，架設一個實際的實驗環境。在選擇無線基地台方面，利用無線網卡的監聽模式蒐集環境的資訊，以期選擇目前最佳的基地台；而在使用無線網路的過程中，除了利用速率的調變來提升效能外，也採用動態的訊框切割幫助效能的提升。除此之外，本篇論文還利用預估頻寬作為目前無線網路環境的知覺標準，當預估頻寬小於設定的標準時，則會切換至監聽模式，重新選擇一個更好的基地台。透過實地的實驗，驗證了此架構的可運行性，實驗數據亦顯示較既有的架構有更好的效能。

Over the past few years, there has been a tremendous growth in the market of mobile computing devices exemplified by the laptop computers. Also the ease of installation and low cost of IEEE 802.11 network, contribute to the enormous growth in the adoption of WLAN. Amid this trend, High-Density WLAN has emerged, which comprises of a large number of Access Points (APs). However, with the current connection architecture, we select an AP among such High-Density WLAN only base on signal strength, which can lead to bad performance due to its ignorance of the load at different APs. Moreover, due to existences of noise and interferences, frame errors occur quite often which makes the performance suffers and current architecture only uses rate adaptation to improve the performance.

In this thesis, we propose a new connection architecture, which use monitor mode to collect environment information for AP selection, also adopt rate adaptation and dynamic fragment threshold to improve the performance while condition getting worse. Furthermore, we use estimated bandwidth as a criterion of condition awareness. We use three access points, and four notebooks and a cordless phone as interference to setup practical scenario. Our experiments show that the proposed architecture works well and has better performance than original architecture.

Contents
中文摘要 ..........................................................................................................................i
Abstract ………………………………………………………………………………....ii
Contents ………………………………………………………………………………..iii
List of Figures ………………………………………………………………………….iv
List of Tables …………………………………………………………………………vi

Chapter 1 Introduction ………………………………………………………………..1
1.1 Background …………………………………………………………………...1
1.2 Motivation ……………………………………………………………………3
1.3 Organization ………………………………………………………………….4
Chapter 2 Related Works ……………………………………………………………..5
2.1 Access Point Selection ……………………………………………………….5
2.2 Rate Adaptation ………………………………………………………………7
2.3 Frame Length Adjustment …………………………………………………..10
Chapter 3 Smart Connection Architecture …………………………………………14
3.1 Original Architecture ………………………………………………………..14
3.2 Description of Smart Connection Architecture ……………………………..15
3.2.1 Smart Connection Architecture-Phase1 ………………………….16
3.2.2 Smart Connection Architecture-Phase2 ………………………….23
3.2.3 Smart Connection Architecture-Phase3 ………………………….28
3.3 Summary ……………………………………………………………………..30
Chapter 4 Experiments and Results ………………………………………………...32
4.1 Access Points Selection and Condition Awareness …………………………32
4.2 Adaptive Mechanism-Rate Adaptation & Frame Length Adjustment ………38
Chapter 5 Conclusion ……………………………………………………………….47
References ……………………………………………………………………………..48

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[2] IEEE 802.11b, “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: High-speed Physical Layer Extension in the 2.4GHz Band,” Supplement to IEEE Standard, September 1999.

[3] IEEE 802.11a, “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: High-speed Physical Layer in the 5GHz band,” Supplement to IEEE Standard, September 1999.

[4] IEEE 802.11g, “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Further Higher Data Rate Extension in the 2.4GHz Band,” Supplement to IEEE Standard, June 2003.

[5] X. G. Jing Zhu, Benjamin Metzler and Y. Liu., “Adaptive CSMA for Scalable Network Capacity in High-Density WLAN: a Hardware Prototyping Approach,” IEEE INFOCOM 2006, April 2006

[6] Glenn Judd, Peter Steenkiste, “Fixing 802.11 Access Point Selection,” ACM SIGCOMM’02, vol.32, pp.31, July 2002.

[7] Y. Fukuda T. Abe, and Y. Oie, “Decentralized Access Point Selection Architecture for Wireless LANs,” In the Proceedings of WTS 2004, SA3, May 2004.

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[11] G. Holland, N. Vaidya, and P. Bahl, “A Rate-Adaptive MAC protocol for Multi-Hop Wireless Networks,” Proc. ACM MobiCom’01, pp.236-251, July 2001.

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[16] Byung-Seo Kim, Yuguang Fang, Wong, T.F., Younggoo Kwon, “Throughput Enhancement Through Dynamic Fragmentation in Wireless LANs,” IEEE Transactions on Vehicular Technology, vol. 54, pp1415-1425, July 2005.

[17] Hsiuen-Yi Chou, Eric Hsiao-Kuang Wu, and Gen-Huey Chen, “Throughput Enhancement for a Noisy WLAN with SNR Based Frame Length Adjustment,” NTU Master’s Thesis, 2005

[18] Yong Xi, Ji-Bo Wei, Zhao-Wen Zhuang, and Byung-Seo Kim, “Performance Evaluation, Improvement and Channel Adaptive Strategy for IEEE 802.11 Fragmentation Mechanisms,” Proc. IEEE ISCC’06, pp142-148, June 2006.

[19] Iperf, http://dast.nlanr.net/Projects/Iperf/

[20] Rtl818x, http://rtl8180-sa2400.sourceforge.net/

[21] Deployment Guide: Cisco Aironet 1000 Series Lightweight Access Points, http://www.cisco.com/univercd/cc/td/doc/product/wireless/hah_apdg/index.htm

[22] Packet Pair Technique,
http://www.hpl.hp.com/personal/Kevin_Lai/projects/nettimer/publications/usits2001/node2.html