由於行動用戶的行動預測對於資源預留、換手管理、預先資源配置等方面皆扮演了 關鍵的角色，目前本文的系統架構中傴以預測行動用戶的未來位置為目標，未來可考慮 透過行動預測機制，於以下項目進行改善：
最佳化預先配置：在通訊過程中，當目標基地台預先配置連線資源時，可針對基地
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台通訊能力、網路壅圔情形與行動用戶個人需求等，於連線資源、頻道分配、服務 品質（Quality of Service, QoS）各方面進行最佳化規劃，進而提升整體網路通訊時 的處理效率與傳輸效能。
協助基地台換手管理：透過行動預測機制，可事先傳遞換手所需的控制訊息及資源 預留，降低換手時的資料傳遞帄均延遲時間與封包遺失率，可促進更帄滑（smooth）
甚至無縫式（seamless）的換手。
考慮不同環境的行動預測：除了本文所探討的都市街道環境，亦可就真實世界中其 他 VANET 環境進行行動預測，例如交通流量稀少的鄉村道路環境、行車速度較高 的高速公路環境等進行討論。
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參考文獻
[1] T. Yasser, et.al, “Vehicle Ad Hoc Networks-Applications and Related Technical Issues,”
IEEE Communications Surveys and Tutorials Magazine, Vol. 10, No. 3, pp. 74-88, 2008.
[2] B. Abderrahim, B. Saman, and A. Chadi, “An Efficient Routing Protocol for Connecting Vehicular Networks to the Internet,” IEEE Journal Selected Areas in Communications, Vol. 29, No. 3, pp. 559-570, 2011.
[3] J. Blum, A. Eskandarian, and L. Hoffmman, “Challenges of Inter-Vehicle Ad hoc Networks,” IEEE Transactions on Intelligent Transportation Systems, Vol. 5, No. 4, pp.
347-351, Dec. 2004.
[4] M. L. Sichitiu and M. Kihl, “Inter-Vehicle Communication Systems: a Survey,” IEEE Communications Surveys and Tutorials Magazine, Vol. 10, No. 2, pp. 88-105, 2008.
[5] H. Moustafa and Y. Zhang, “Vehicular Networks-Techniques, Standards, and Applications,” 2009.
[6] Cloud Computing, http://searchcloudcomputing.techtarget.com/sDefinition.html/, Nov.
2009.
[7] ZD net, “Google to Go Carbon Neutral by 2008,” http://news.zdnet.co.uk/internet.htm/, Jun. 2007.
[8] B. S. Belz, et.al, “Intelligent Brokering of Tourism Services for Mobile Users,”
Proceedings of Federation on Information Technology in Tourism, Jan. 2002.
[9] D. Ashbrook and T. Starner, “Learning Significant Locations and Predicting User Movement with GPS,” Proceedings of Wearable Computers, pp. 101-108, Oct. 2002.
[10] N. Marmasse and C. Schmandt, “A User-Centered Location Model,” Personal and Ubiquitous Computing, Vol. 6, pp. 318-321, Dec. 2002.
[11] N. Samaan, “A Mobility Prediction Architecture Based on Contextual Knowledge and Spatial Conceptual Maps,” IEEE Transactions on Mobile Computing, Vol. 4, pp.
537-551, 2005.
[12] M. S. Sricharan, V. Vaidehi, and P. P. Arun, “An Activity based Mobility Prediction Strategy for Next Generation Wireless Networks,” IFIP International Conference on Wireless and Optical Communications Networks, pp. 1-5, Aug. 2006.
[13] P. S. Prasad, et.al, “A Generic Framework for Mobility Prediction and Resource Utilization in Wireless Networks,” IEEE International Conference on Communication Systems and Networks, pp. 1-10, Jan. 2010.
[14] 鍾享材, “A Light-Weight Moving Preferences Based Dynamic Location Management Scheme Using Road Map and GPS,” 中央大學資訊工程研究所碩士論文, 2004.
67
[15] M. H. Khaledi, et al. “Mobility Aware Distributed Topology Control in Mobile Ad-Hoc Networks Using Mobility Pattern Matching,” IEEE International Conference on Wireless and Mobile Computing, 2009.
[16] Y. Yuan, et.al, “A Novel Mobility Prediction Mechanism in Heterogeneous Networks,”
IEEE International Conference on Communications and Mobile Computing (CMC), pp.
536-540, Apr. 2010.
[17] P. S. Prasad, et.al, “Mobility Prediction for Wireless Network Resource Management,”
IEEE Southeastern Symposium on System Theory, pp. 98-102, Mar. 2009.
[18] G.P. Pollini and C. Lin, “A Profile-based Location Strategy and Its Performance,” IEEE Journal on Selected Areas in Communications, Vol. 15, pp. 1415-1424, Oct. 1997.
[19] M. H. Jin, E. H. Kuang and J. T. Horng, “Location Query based on Moving Behavior,”
International Conference on Computer Communications and Networks, pp. 268-273, Oct.
2002.
[20] H. K. Wu, et.al, “Personal Paging Area Design based on Mobile's Moving Behaviors,”
Annual Joint Conference of the IEEE Computer and Communications Societies, Vol. 1, pp. 21-30, Apr. 2001.
[21] W. S. Soh and H. S. Kim, “QoS Provisioning in Cellular Networks based on Mobility Prediction Techniques,” IEEE Communications Magazine, pp. 86-92, Jan. 2003.
[22] W. S. Soh and H. S. Kim, “Dynamic Bandwidth Reservation in Cellular Networks Using Road Topology Based Mobility Predictions,” IEEE International Conference, Mar.
2004.
[23] J Zhao, “VADD: Vehicle-assisted Data Delivery in Vehicular Ad Hoc Networks,” IEEE Transactions on Vehicular Technology, 2008.
[24] H. Ghazale et.al, “Application of Mobility Prediction in Wireless Networks Using Markov Renewal Theory,” 2009.
[25] S. M. Mousavi, et.al, “Mobility Aware Distributed Topology Control in Mobile Ad-Hoc Networks with Model Based Adaptive Mobility Prediction,” IEEE International Conference on Wireless and Mobile Computing, pp. 86-86, Oct. 2007.
[26] Z. Mir, et.al, “Mobility Aware Distributed Topology Control for Mobile Multi-hop Wireless Networks,” Springer Lecture Notes in Computer Science, pp. 257-266, 2006.
[27] D. Son, A. Helmy, B. Krishnamachari, “The Effect of Mobility-induced Location Errors
on Geographic Routing in Mobile Ad Hoc Sensor Networks: Analysis and Improvement Using Mobility Prediction,” IEEE Transactions on Mobile Computing, Vol. 3, No. 3, pp.
233-245, Aug. 2004.
[28] W. Su, et.al, “Mobility Prediction and Routing in Ad hoc Wireless Networks,”
International Journal of Network Management, Vol. 11, No. 1, pp.3-30, 2001.
68
[29] F. Bai, et.al, “The Important Framework for Analyzing the Impact of Mobility on Performance of Routing Protocols for Adhoc Networks,” Elsevier Journal of Ad Hoc Networks, pp. 383-403, 2003.
[30] T. Camp, et.al, “A Survey of Mobility Models for Ad Hoc Network Research,”
Wireless Communication and Mobile Computing, Vol. 2, No. 5, pp. 483-502, 2002.
[31] S. M. Mousavi, et.al, “MobiSim: A Framework for Simulation of Mobility Models in Mobile Ad-Hoc Networks,” IEEE international Conference on Wireless and Mobile Computing, Oct. 2007.
[32] “MATLAB - The Language Of Technical Computing,” http://www.mathworks.com/
products /matlab/
[33] Y. L. Tang, “Dividing Sensitive Ranges based Mobility Prediction Algorithm in Wireless Networks,” 2010.
[34] M. Chegin, et.al, “Optimized Routing based on Mobility Prediction in Wireless Mobile Adhoc Networks for Urban Area,” IEEE International Conference on Information Technology, pp. 390-395, Apr. 2008.
[35] IEEE 802.21 (Media Independent Handover Services), http://www.ieee802.org/21/
[36] S. Bellahsene and L. Kloul, “A New Markov-Based Mobility Prediction Algorithm for Mobile Networks,” Computer Performance Engineering, Vol. 6342, pp. 37-50, 2010.
[37] S. Bo and L. Yun, “Movement Prediction Model Based on HMM and Simulations,”
Journal of System Simulation, Vol. 19, No. 18, 2007.
[38] 徐振煒, “以隱藏式馬克夫模型預測行動通訊使用者的移動樣式,” 逢甲大學資訊電
機工程研究所碩士論文, 2009.
[39] M. K. Marina and S. R. Das, “On-Demand Ad hoc Multi-Path Distance Vector Routing Protocol,” Proceedings of IEEE International Conference, 2001.
[40] A. Hamidian, “Performance of Internet Access Solutions in Mobile Ad Hoc Networks,”
2005.
[41] C. Perkins, E. Belding-Royer, and S. Das, “Ad hoc On-Demand Distance Vector (AODV) Routing,” Network Working Group, RFC 3561, Jul. 2003.
[42] R. Durbin, et.al, “Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids,” Cambridge University Press, 1999.
[43] L. R. Rabiner, “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,” Proceedings of the IEEE, Vol.77, No. 2, pp. 257-286, Feb. 1989.
[44] N. Shokhirev, “Hidden Markov Models,” http://www.shokhirev.com/nikolai/abc/alg/
hmm /hmm.html/, 2010.
69
[45] F. Bai, N. Sadagopan, and A. Helmy, “IMPORTANT: a Framework to Systematically Analyze the Impact of Mobility on Performance of Routing Protocols for Ad Hoc Networks,” Proceedings of IEEE Information Communications Conference, Vol. 2, pp.
825-835, Apr. 2003.
[46] W. J. Hsu and A. Helmy, “MobiLib: Community-wide Library of Mobility and Wireless Networks Measurements (Investigating User Behavior in Wireless Environments),”
http://nile.cise.ufl.edu/MobiLib, Aug. 2005.
[47] G. D. Forney, “The Viterbi Algorithm,” Proceedings of the IEEE, Vol. 61, No.3, pp.268-278, Mar. 1973.
[48] The Network Simulator (NS-2), http://www.isi.edu/nsnam/ns, release 2.1b9a, Jul. 2002.