IEEE 802.11無線區域網路的行動性(mobility)一直是許多人關注的議題，如何在行進中保持與網路的穩定連線並且任由使用者在無線基地台之間平穩地漫遊更是許多人的需求。這篇論文提出了一個在802.11 WLAN環境下的完整換手(handoff)系統架構。我們利用802.11 WLAN的無線訊號實做定位系統(Positioning System)，用來追蹤使用者位置以及記錄使用者的移動習慣，並以我們所提出的運動預測模型(Motion Prediction Model)分析推測使用者接下來可能的移動情況，提供適合連結的無線基地台給行動裝置，作為handoff的決策依據。這篇論文所提出的運動預測模型，是結合了使用者以往的移動習慣以及目前的移動方向，推算出接下來可能的行進方式; 再根據可能的行進方式，計算出適當的無線基地台連結優先順序。因此能夠符合使用者的移動情況，無線裝置能夠獲得有效的行動存取資訊，降低了不必要的handoff發生機會，延長無線裝置與無線基地台的連結保持時間，因而提升了每次handoff的實質效益。我們也實際實作了此系統, 稱為Mobility Auto-Configuration (MAC) System, 用來驗證我們所提出的系統架構是可行的，並且具備低成本建置的優點，因此符合本研究的期許目標。

The mobility issue of the IEEE 802.11 wireless LAN is a popular topic to many people. The mobile users who have to roam from place to place hope to access to the networks stably and smoothly; however, there are still lots of challenges have to be overcome. This paper proposes a complete handoff system architecture for 802.11 WLAN. We design an 802.11 based positioning system, which can locate the location of mobile users by analyzing the received signal patterns. Thus, we can track and record the moving patterns of mobile users. A mobility prediction model is proposed, called Motion Prediction Model, which predict possible movement of the mobile user by analyzing the location information from the positioning system. We use the predicted movement result to estimate and prioritize a set of candidate access points and forward them to the mobile user for handoff decision. The proposed Motion Prediction Model combines the history moving patterns and current moving direction of the mobile user, and then predicts the next movement of the mobile user. Latter, we take advantage of the predicted movement to estimate a proper set of candidate access points for handoff request from the mobile user. Thus, the prediction conform the moving pattern to the mobile user, and the mobile user can get efficient mobility information to reduce unnecessary handoffs and prolong the time which the mobile user keeps connecting to an access point. Hence, it is really an enhanced handoff architecture for improving the performance of the handoff decision. We also implement the proposed system architecture, called Mobility Auto-Configuration (MAC) System, for testing and verifying. We can show that it is a feasible solution to build an efficient mobile computing system and it just takes low cost. It really provides better performance than traditional handoff algorithms in our experiment, so we improve the handoff process, and allow higher mobility for 802.11 WLAN.

[1] G. Anastasi, R. Bandelloni, M. Conti, F. Delmastro, E. Gregori, and G. Mainetto, “Experimenting an Indoor Bluetooth-based Positioning Service,” IEEE Proc. Distributed Computing Systems Workshops, pp. 480-483, May 2003.

[2] J. Hallberg, M. Nilsson, and K. Synnes, “Positioning with Bluetooth,” the 10th International Conference on Telecommunications (ICT), 2003.

[3] M. Hazas, and A. Hopper, “Broadband Ultrasonic Location Systems for Improved Indoor Positioning,” IEEE Transactions on Mobile Computing, pp. 536-547, May 2006.

[4] A. Krohn, M. Beigl, M. Hazas, and H.W. Gellersen, “Using Fine-Grained Infrared Positioning to Support the Surface-Based Activities of Mobile Users,” IEEE Distributed Computing Systems Workshops, pp. 463-468, June 2005.

[5] H.D. Chon, S. Jun, H. Jung, and S.W. An, “Using RFID for Accurate Positioning, ” Journal of Global Positioning Systems (CPGPS), pp. 32-39, Feb. 2005.

[6] P. Bahl and V.N. Padmanabhan, “RADAR：An In-Building RF-based User Location and Tracking System,” Proc. IEEE INFOCOM, pp. 775-784, 2000.

[7] K. Kaemarungsi and P. Krishnamurthy, “Properties of Indoor Received Signal Strength for WLAN Location Fingerprinting,” Proc. IEEE MobiQuitous, 2004.

[8] G.P. Pollini, “Trends in Handover Design,” IEEE Communications Magazine, pp. 82-90, March 1996.

[9] J.C. Wu, C. Cheng, and N. Huang, “Intelligent Handoff for Mobile Wireless Internet,” Mobile Networks and Applications, no. 6, pp. 67-79, 2001.

[10] K.E. Malki. “Low latency handoffs in mobile ipv4,” Technical report, draft- ietf-monileip-lowlatency-handoffsv4-03.txt, IETF Internet draft, Nov. 2001.

[11] C.T. Chou, K.G. Shin, “An Enhanced Inter-Access Point Protocol for Uniform Intra and Intersubnet Handoffs,” IEEE Transactions on Mobile Computing, vol. 04, no. 4, pp. 321-334, Jul-Aug, 2005.

[12] R. Hsieh, Z.G. Zhou, and A. Seneviratne, “S-MIP: A Seamless Handoff Architecture for Mobile IP,” IEEE Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), pp. 1774- 1784, 2003.

[13] T. Lin, C. Wang, and P.C. Lin, “A Neural Network Based Context-Aware Handoff Algorithm for Multimedia Computing,” Proc. IEEE Acoustics, Speech, and Signal Processing (ICASSP), 2005.

[14] G. Liu and G. Maguire, “A class of mobile motion prediction algorithms for wireless mobile computing and communications,” ACM Portal Mobile Networks and Applications, vol. 1, no. 2, pp. 113-121, 1996.

[15] Z. Cen, H. Chen, and X. Lin, “Motion Prediction in Mobile Communication Systems from a Historical and Geographical Perspective,” CSE812 (Advanced Operating Systems) term project, Michigan State University, 2002.

[16] N. Samaan, A. Karmouch, “A Mobility Prediction Architecture Based on Contextual Knowledge and Spatial Conceptual Maps,” IEEE Transactions Mobile Computing, vol. 4, no. 6, pp. 537-551, Nov. 2005.

[17] T. Liu, P. Bahl and I. Chlamtac, “Mobility Modeling, Location Tracking, and Trajectory Prediction in Wireless ATM Networks,” IEEE Journal on Selected Areas in Communications (JSAC), vol. 16, no. 6, pp. 922-936, Aug. 1998.

[18] V. Kumar and P. Venkataram, “Prediction-based location management using multilayer neural networks,” J. Indian Institute of Science, vol. 82, no. 1, pp. 7-21, 2002.

[19] G. Yavas, D. Katsaros, Ö. Ulusoy, and Y. Manolopoulos, “A data mining approach for location prediction in mobile environments,” ACM Portal Data & Knowledge Engineering, vol. 54, pp. 121-146, Aug. 2005.

[20] C. Tuduce and T. Gross, “A Mobility Model Based on WLAN Traces and its Validation,” IEEE Proc. INFOCOM 2005, vol. 1, pp. 664-674, March 2005.

[21] S. Pack and Y. Choi, “Fast handoff scheme based on mobility prediction in public wireless LAN systems,” IEE Proc. Communications, pp. 489-495, Oct. 2004.

[22] C.C. Tseng, K.H. Chi, M.D. Hsieh, and H.H. Chang, “Location-based Fast Handoff for 802.11 Networks,” IEEE Communications Letters, pp. 304-306, April 2005.

[23] Microsoft Corp., “IEEE 802.11 Network Adapter Design Guidelines for Windows XP”, Seattle, WA. Microsoft Corp., http://www.microsoft.Com/whdc/ hwdev/tech/network/802x/80211_netadapt.mspx, May 2003.