Publications-Theses
Article View/Open
Publication Export
-
Google ScholarTM
NCCU Library
Citation Infomation
Related Publications in TAIR
題名 結合藍牙低功耗的 IEEE 802.11無線網路負載平衡機制
Load Balance for IEEE 802.11 Wireless LAN with Bluetooth Low Energy作者 李致賢
Lee, Chih Hsien貢獻者 張宏慶
李致賢
Lee, Chih Hsien關鍵詞 無線區域網路
802.11通訊協定
負載平衡
藍牙低功耗
Wireless
IEEE 802.11
Load Balance
Bluetooth Low Energy日期 2015 上傳時間 2-Dec-2015 16:09:41 (UTC+8) 摘要 在使用者較為密集的場合中，常會碰到無線網路壅塞的問題，例如在一個大型會議廳中，常會在各個IEEE 802.11頻道上部署不同的WiFi AP（Access Point），來分散使用者的連線。但是由於IEEE 802.11的連線機制是屬於使用者主導（client driven），只能透過使用者去選定AP進行連線，對於使用者裝置來說,，連線到不同AP的優先順序，是依照接收到不同AP的信號強度（RSSI）作為排序指標。這種做法會讓在空間上使用者分佈不平均的環境中，造成多數使用者UE只連線到少數AP，而其餘AP資源閒置無用的情形。 本論文提出一個IEEE 802.11的負載平衡解決方案，結合藍牙低功耗（Bluetooth Low Energy，BLE）及IEEE 802.11成為一個智慧型AP架構。我們利用藍牙低功耗通訊協定GATT （Generic Attribute Profile）分派AP給不同使用者進行連線，再結合馬可夫鏈平穩狀態分佈（Markov Chains Stationary Distribution）演算法，依照使用者在AP網路拓樸中的歷史分佈紀錄，將多個AP的分派轉化為Erlang-C模型的排隊系統以計算AP分派規則，藉此達到系統的負載平衡。
Usually, a user crowded space encounters wireless network congestion problem. For example, a large conference hall often deploys different wireless AP (Access Point) on each IEEE 802.11 channel to separate users’ connections. However, since the connection mechanism of IEEE 802.11 is client driven, the AP connection is selected by the user and the selection is according to the received signal strength(RSSI) from different APs. This conventional approach may result in most of the user devices connect to relatively limited number of APs, and the resource of the rest of the APs left unused. This paper proposes a smart AP architecture which is able to manage load balance for IEEE 802.11 Wireless LAN using Bluetooth Low Energy (BLE) GATT (Generic Attribute Profile) protocol in order to appropriatelyassign AP to different user devices. The core AP assignment algorithm is based on Markov chain stationary distribution. Simulation results show that the proposed BM-MS (BLE Management with Markov-Chains Stationary Load Balance) method outperforms RSSI based method in terms of system throughput and average user data rate.參考文獻 1. Thomas R. Robbins and D. J. Medeiros, “Does The Erlang-C Model Fit In Real Call Centers?,” Simulation Conference (WSC), Proceedings of the 2010 Winter, 2010.2. I. Papanikos and M. Logothetis, “A Study on Dynamic Load Balance for IEEE 802.11b Wireless LAN,” Proc. Int`l Conf. Comm. Control (COMCON `01), 2001.3. Li-Hsing Yen, Tse-Tsung Yeh, and Kuang-Hui Chi, “ Load Balancing in IEEE 802.11 Networks” Internet Computing, IEEE , 2009.4. P. Bahl, WA. Redmond, K. Jain, et al., “Cell Breathing in Wireless LANs: Algorithms and Evaluation,” Mobile Computing, IEEE Transactions on, 2007.5. T-C. Tsai and C-F. Lien, “IEEE 802.11 Hot Spot Load Balance and QoS Maintained Seamless Roaming,” In Proc. National Computer Symposium (NCS), 2003.6. Anand Balachandran, Geoffrey M. Voelker, Paramvir Bahl, and P. Venkat Rangan, “Characterizing User Behavior and Network Performance in a Public Wireless LAN,” SIGMETRICS `02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, 2002.7. M. Afanasyev et al., “Usage Patterns in an Urban WiFi Network,” IEEE/ACM Trans. Netw., vol. 18, no. 5, pp. 1359–1372, Oct, 2010.8. K.A. Magade, A. Patankar,“Techniques for Load Balancing in Wireless LAN`s,” Communications and Signal Processing (ICCSP), 2014 International Conference on, April 2014.9. Y. Bejerano, Seung-Jae Han, Li Li, “Fairness and Load Balancing in Wireless LANs Using Association Control,” Networking, IEEE/ACM Transactions on (Volume:15 , Issue: 3 )10. A.K. Rangisetti, H.B. Baldaniya, B.P. Kumar, B.R. Tamma, “Load-aware Hand-offs in Software Defined Wireless LANs,” Wireless and Mobile Computing, Networking and Communications (WiMob), 2014 IEEE 10th International Conference on, Oct. 2014. 描述 碩士
國立政治大學
資訊科學學系
102753008資料來源 http://thesis.lib.nccu.edu.tw/record/#G0102753008 資料類型 thesis dc.contributor.advisor 張宏慶 zh_TW dc.contributor.author (Authors) 李致賢 zh_TW dc.contributor.author (Authors) Lee, Chih Hsien en_US dc.creator (作者) 李致賢 zh_TW dc.creator (作者) Lee, Chih Hsien en_US dc.date (日期) 2015 en_US dc.date.accessioned 2-Dec-2015 16:09:41 (UTC+8) - dc.date.available 2-Dec-2015 16:09:41 (UTC+8) - dc.date.issued (上傳時間) 2-Dec-2015 16:09:41 (UTC+8) - dc.identifier (Other Identifiers) G0102753008 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/79525 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊科學學系 zh_TW dc.description (描述) 102753008 zh_TW dc.description.abstract (摘要) 在使用者較為密集的場合中，常會碰到無線網路壅塞的問題，例如在一個大型會議廳中，常會在各個IEEE 802.11頻道上部署不同的WiFi AP（Access Point），來分散使用者的連線。但是由於IEEE 802.11的連線機制是屬於使用者主導（client driven），只能透過使用者去選定AP進行連線，對於使用者裝置來說,，連線到不同AP的優先順序，是依照接收到不同AP的信號強度（RSSI）作為排序指標。這種做法會讓在空間上使用者分佈不平均的環境中，造成多數使用者UE只連線到少數AP，而其餘AP資源閒置無用的情形。 本論文提出一個IEEE 802.11的負載平衡解決方案，結合藍牙低功耗（Bluetooth Low Energy，BLE）及IEEE 802.11成為一個智慧型AP架構。我們利用藍牙低功耗通訊協定GATT （Generic Attribute Profile）分派AP給不同使用者進行連線，再結合馬可夫鏈平穩狀態分佈（Markov Chains Stationary Distribution）演算法，依照使用者在AP網路拓樸中的歷史分佈紀錄，將多個AP的分派轉化為Erlang-C模型的排隊系統以計算AP分派規則，藉此達到系統的負載平衡。 zh_TW dc.description.abstract (摘要) Usually, a user crowded space encounters wireless network congestion problem. For example, a large conference hall often deploys different wireless AP (Access Point) on each IEEE 802.11 channel to separate users’ connections. However, since the connection mechanism of IEEE 802.11 is client driven, the AP connection is selected by the user and the selection is according to the received signal strength(RSSI) from different APs. This conventional approach may result in most of the user devices connect to relatively limited number of APs, and the resource of the rest of the APs left unused. This paper proposes a smart AP architecture which is able to manage load balance for IEEE 802.11 Wireless LAN using Bluetooth Low Energy (BLE) GATT (Generic Attribute Profile) protocol in order to appropriatelyassign AP to different user devices. The core AP assignment algorithm is based on Markov chain stationary distribution. Simulation results show that the proposed BM-MS (BLE Management with Markov-Chains Stationary Load Balance) method outperforms RSSI based method in terms of system throughput and average user data rate. en_US dc.description.tableofcontents 誌謝 1中文摘要 2Abstract 3CONTENTS 4圖目錄 7Chapter 1 緒論 9Chapter 2 背景知識 112.1 IEEE 802.11 112.1.1 IEEE 802.11 網路架構簡介 112.1.2 精簡型無線網路（Thin AP）架構 122.2 藍牙低功耗（Bluetooth Low Energy） 132.2.1 簡介 132.2.2 藍牙低功耗的架構與通訊協定 142.2.3 藍牙低功耗的設備運作流程 152.2.4 GATT（Generic Attribute Profile）通訊協定 162.2.5 廣播封包（Advertising） 172.3 排隊系統與馬可夫鏈模型 202.3.1 M/M/c排隊模型（Erlang-C 模型） 202.3.2 M/M/c 排隊系統的平穩狀態分析 （Stationary） 21Chapter 3 相關研究 233.1 IEEE 802.11基礎架構中的連線機制 233.2 現有IEEE 802.11負載平衡機制 243.2.1 WS-based Load Distribution 243.2.2 Network-based Load Distribution 253.3 公共WLAN中的使用者行為分析 26Chapter 4 方法論 294.1 結合藍牙低功耗的WLAN連結管理方法 294.1.1 負載平衡架構設計 304.1.2 負載平衡架構的可行性。 334.2 負載平衡（BM-MS）核心演算法 374.2.1 Erlang-C 模型與使用者行為假設 374.2.2 演算過程 394.2.3 分派流程 42Chapter 5 模擬驗證 455.1 實驗條件 455.2 模擬環境介紹 475.2.1 SimPy – 離散時間事件模擬 475.2.2 NS3 – Network Simulator 3 485.3 模擬結果分析 505.3.1 拓樸變化 505.3.2 實驗結果比較 525.4 模擬結果 53Chapter 6 結論與未來研究 54參考資料 56 zh_TW dc.format.extent 3802564 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0102753008 en_US dc.subject (關鍵詞) 無線區域網路 zh_TW dc.subject (關鍵詞) 802.11通訊協定 zh_TW dc.subject (關鍵詞) 負載平衡 zh_TW dc.subject (關鍵詞) 藍牙低功耗 zh_TW dc.subject (關鍵詞) Wireless en_US dc.subject (關鍵詞) IEEE 802.11 en_US dc.subject (關鍵詞) Load Balance en_US dc.subject (關鍵詞) Bluetooth Low Energy en_US dc.title (題名) 結合藍牙低功耗的 IEEE 802.11無線網路負載平衡機制 zh_TW dc.title (題名) Load Balance for IEEE 802.11 Wireless LAN with Bluetooth Low Energy en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 1. Thomas R. Robbins and D. J. Medeiros, “Does The Erlang-C Model Fit In Real Call Centers?,” Simulation Conference (WSC), Proceedings of the 2010 Winter, 2010.2. I. Papanikos and M. Logothetis, “A Study on Dynamic Load Balance for IEEE 802.11b Wireless LAN,” Proc. Int`l Conf. Comm. Control (COMCON `01), 2001.3. Li-Hsing Yen, Tse-Tsung Yeh, and Kuang-Hui Chi, “ Load Balancing in IEEE 802.11 Networks” Internet Computing, IEEE , 2009.4. P. Bahl, WA. Redmond, K. Jain, et al., “Cell Breathing in Wireless LANs: Algorithms and Evaluation,” Mobile Computing, IEEE Transactions on, 2007.5. T-C. Tsai and C-F. Lien, “IEEE 802.11 Hot Spot Load Balance and QoS Maintained Seamless Roaming,” In Proc. National Computer Symposium (NCS), 2003.6. Anand Balachandran, Geoffrey M. Voelker, Paramvir Bahl, and P. Venkat Rangan, “Characterizing User Behavior and Network Performance in a Public Wireless LAN,” SIGMETRICS `02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, 2002.7. M. Afanasyev et al., “Usage Patterns in an Urban WiFi Network,” IEEE/ACM Trans. Netw., vol. 18, no. 5, pp. 1359–1372, Oct, 2010.8. K.A. Magade, A. Patankar,“Techniques for Load Balancing in Wireless LAN`s,” Communications and Signal Processing (ICCSP), 2014 International Conference on, April 2014.9. Y. Bejerano, Seung-Jae Han, Li Li, “Fairness and Load Balancing in Wireless LANs Using Association Control,” Networking, IEEE/ACM Transactions on (Volume:15 , Issue: 3 )10. A.K. Rangisetti, H.B. Baldaniya, B.P. Kumar, B.R. Tamma, “Load-aware Hand-offs in Software Defined Wireless LANs,” Wireless and Mobile Computing, Networking and Communications (WiMob), 2014 IEEE 10th International Conference on, Oct. 2014. zh_TW
