無線車輛感測網路(wireless vehicular sensor network ;VSN) 是一個在促進傳輸應用發展非常有用的系統。它有別於一般傳統無線感測網路的運作,基本上VSN不太會受到電源的侷限，除了維持訊息傳輸穩定外，更多更重要的安全緣由，確保車輛與車輛間以及車輛與通訊閘道間穩定的連線是必須的，也因此車輛感測網路系統的發展在受到漫遊的環境以及種種不確定交通因素影響下成了一項挑戰，使得如何保持連線的穩定就成為一個重要的議題。在這篇論文中，提出一個藉由灰預測目標循跡的預先繞徑機制，冀期在連線失敗之前能及時運用再繞徑或變換路徑以強化連線，確保車輛感測網路的更趨於穩定。雖然，這一機制因採用灰預測目標循跡而增加了平均的延遲時間(latency)也加重了控制信號(control overhead)的處理，但它確確實實提供了更佳的存活能力和再繞徑的更快速反應。

The wireless vehicular sensor network (VSN) is very useful and promoted for many transportation application systems. However, it does not operate like the traditional wireless sensor network which limited in the power saving. For more important reason on safety, vehicle-vehicle and vehicle-gateway communication must be stable on linking. For the scenario of the vehicle network, the environment with roaming roads and other uncertain traffic conditions which challenges the system. Therefore, how to keep link stability becomes an essential issue. In this thesis, we propose a pre-route scheme with grey target tracking in advance to re-route weak links to alternative routes before failure occurs, i.e., make the vehicular sensor network more stable. Although this scheme increases average latency and control overhead, with grey target tracking, it supports higher survivability and faster reflection on re-routing.

Chapter 1 Introduction....................................1
1.1 Background of Vehicular Sensor Networks........................................1
1.1.1 Inter-Vehicle Communication and Vehicle-to-Road Communication ..............................1
1.1.2 Combined Vehicular Communication...................................5
1.1.3 Vehicular Mesh Networks........................................6
1.2 Motivation..................................8
1.3 Organization................................9
Chapter 2 Target Tracking.......................................11
2.1 Target Tracking.......................................11
2.1 1 Tracking Moving Target.........................................11
2.1.2 Tracking Steps..........................................12
2.2Multicasting.................................................................................14
2.2.1 Multicast Ad Hoc On-Demand distance Vector Protocol (MAODV)........................................18
2.2.2 On-Demand Multicast Routing Protocol (ODMRP)........................................20
Chapter 3 Grey System.........................................25
3.1 Concept of Grey System.........................................25
3.2 Characteristics of Grey System.........................................25
3.3 MGO vs. IMGO and AGO vs. IAGO...........................................27
3.4 Construct the Grey prediction model GM (1,1)..........................................30
3.5 An Example of Grey prediction.....................................35
Chapter 4 The Novel Grey Target Tracking Resilient Routing (GTTRR) Protocol.......................................38
4.1 Communications in Vehicular Sensor Networks........................................................................................38
4.2 RREQ & RREP...........................................39
4.3 GTTRR Procedure......................................41
Chapter 5. Simulations and Analysis.......................................46
5.1 Simulation parameters.....................................46
5.2 Communication Terminologies..................................49
5.3 Simulation Result and Analysis.......................................50
Chapter 6 Conclusion.....................................54
References......................................................................................56
VITA...........................................61

References

[1]H. Alshaer and E. Horlait, “An Optimized Adaptive Broadcast Scheme for Inter-Vehicle Communication,” In Proc. Vehicular Technology Conference, vol. 5, pp. 2840–2844, June 2005.

[2]H. C. Chang, H. Du, J. Anda, C.-N. Chuah, D. Ghosal and H. M. Zhang, “Enabling Energy Demand Response with Vehicular Mesh Networks,” In Proc. Mobile and Wireless Communication Networks, vol. 162, pp. 371–382, October 2004.

[3]J. L. Deng, “Essential Topics on GREY SYSTEM Theory and Application,” Beijing, China: Ocean Press, 1988.

[4]M. Durresi, A. Durresi and L. Barolli, “Sensor Inter-Vehicle Communication for Safer Highways,” In Proc. Advanced Information Networking and Applications 2005, pp. 599–604, March 2005.

[5]R. Gupta and S. R. Das, “Tracking Moving Targets in a Smart Sensor Network,” In Proc. Vehicular Technology Conference, vol.5, pp.3035-3039, April 2003.

[6]U. Lee, E. Magistretti, B. Zhou, M. Gerla, P. Bellavista and A. Corradi, “Efficient Data Harvesting in Mobile Sensor Platforms,” In Proc. Pervasive Computing and Communications Workshop 2006, pp. 352–356, March 2006.

[7]B. Liu, P. Brass, O. Dousse, P. Nain and D. Towsley, “Mobility Improves Coverage of Sensor Networks,” In Proc. International Symposium on Mobile Ad Hoc Networking and Computing, Urbana-Champaign, IL, USA, pp. 300-308, May 2005.

[8]S. D. Muruganathan, D. C. F. Ma, R. I. Bhasin and A. O. Fapojuwo, “A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks,” IEEE Radio Communications Mag., vol. 43, no. 3, pp. s8–13, March 2005.

[9]M. Nekovee, “Sensor Networks on The Road: The Promises and Challenges of Vehicular ad hoc Networks and Grids,” In Proc. Ubiquitous Computing and e-Research, Edinburgh, UK, May 2005.

[10]D. Niculescu, “Communication Paradigms for Sensor Networks,” IEEE Communication Mag., pp. 116–122, March 2005.

[11]H. Saito, “Performance Analysis of Combined Vehicular Communication,” IEICE Trans. Communication, vol.E89-B, no.5, pp.1486-1494, May 2006.

[12]C. C. Wong, B. C. Lin and C. T. Cheng, “Fuzzy tracking method with a switching grey prediction for mobile robot,” In Proc. IEEE International Conference, vol. 1, pp. 103–106, December 2001.

[13]X. Wu, H. Heo, R. A. Shaikh, J. Cho, O. Chae and S. Lee, “Individual Contour Extraction for Robust Wide Area Target Tracking in Visual Sensor Networks,” In Proc. IEEE Int. Sym. on Object and Component-Oriented Real-Time Distributed Computing, April 2006.

[14] S. S. C. Rezaei and B. H. Khalaj, “Grey Prediction Base Handoff Algorithm,” Transactions on Engineering, Computing and Technology, vol.2, pp.80-83, December 2004.

[15] J. L. Deng, “Introduction to grey system theory,” The Journal of Grey System, vol.1, Issue 1, pp.1-24, 1989.

[16]S. L. Su, Y. C. Su and J. F. Huang, “Grey-Based Power Control for DS-CDMA Cellular Mobile Systems,” IEEE Transactions on Vehicular Technology, vol.49, no.6, pp.2081-2088, November 2000.

[17]Y. H. Lin, J. S. Wang and P. F. Pai, “A Grey Prediction Model with Factor Analysis Technique,” Journal of Chinese Institute of Industrial Engineers, vol.21, no.6, pp.535-542, 2004.

[18] Ge. Zhang and W. R. Hamel, “Modeling Tooling Interactions of Teleoperation Using Grey System Theory,” Intelligent Robots and Systems 2005 (IROS 2005), 2005 IEEE/RSJ International Conference, pp.3140–3145, August 2005.

[19]R. C. Luo, T. M. Chen and K. L. Su, “Target tracking using a hierarchical grey-fuzzy motion decision-making method,” Systems, Man and Cybernetics, Part A, IEEE Transactions vol.31, Issue 3, pp.179-186, May 2001.

[20]I. Pavlidis and N. P. Papanikolopoulos, “Automatic selection of control points for deformable-model-based target tracking,” In Proc. IEEE Int. Conf. Robotics Automation, Minneapolis, MN, pp.2915–2920, April 1996.

[21]R. C. Luo and T. M. Chen, “Target tracking by grey prediction theory and look-ahead fuzzy logic control,” Robotics and Automation, 1999. Proceedings 1999 IEEE International Conference, vol.2, pp.1176-1181, May 1999.

[22]T. Goff, N. B. Abu-Ghazaleh, D. S. Phatak and R. Kahvecioglu, “Preemptive Routing in Ad Hoc Networks,” Proceedings of the Seventh Annual International Conference on Mobile Computing and Networking, Rome, Italy, pp.43-52, July 2001.

[23]J. Bardwell, “Converting Signal Strength Percentage to dBm Values,” California, USA: WildPackets, Inc., November 2002.

[24]Y. F. Wang, and L. L. Liu, “Grey Target Tracking on Vehicular Sensor Networks,” In Proc 2006 Symposium On Communication Information Electronics and Applications, pp.135–140, Kaohsiung, Taiwan, ROC., October 2006.

[25]Y. F. Wang, and L. L. Liu, “Grey-based Prerouting and Target Tracking on Vehicular Sensor Networks,” In Proc. 2006 National Symposium on Telecommunications (NST2006), SessionB3, NST-2006-0481.pdf in CDROM, Kaohsiung, Taiwan, ROC., December 2006.

[26]Y. F. Wang, and L. L. Liu, “Grey Target Tracking on Vehicular Sensor Networks,” In Proc. International Conference On Late Advances in Networks (ICLAN’2006), Session Ⅱ Mobility and Localisation in CDROM, Paris, France, December 2006.

[27]A. Steed, S. Spinello, B. Croxford and C. Greenhalgh, “e-Science in the Streets: Urban Pollution Monitoring,” In UK e-Science All Hands Meeting, Nottingham, UK, September 2003.

[28]I. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “A Survey on Sensor Networks,” IEEE Communication Mag., pp.102–114, August 2002.

[29]U. Lee, E. Magistretti, B. Zhou, M. Gerla, P. Bellavista and A. Corradi, “MobEyes: Smart Mobs for Urban Monitoring with Vehicular Sensor Networks,” UCLA CSD Technical Report, IEEE Wireless Communications, vol. 13, No. 5, September 2006

[30]C. E. Perkins and E. M. Royer, “Ad-hoc On-Demand Distance Vector Routing,” Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, New Orleans, LA, pp.90-100. February 1999.

[31]E. M. Royer and C. E. Perkins, “Multicast Operation of the Ad hoc On-Demand Distance Vector Routing Protocol,” Proceedings of MobiCom '99, Seattle, pp.207-218, August 1999.

[32]S. J. Lee, W. Su and M. Gerla, “On-demand Multicast Routing Protocol in Multihop Wireless Mobile Networks,” Mobile Networks and Applications, vol. 7, Issue 6, pp.441-453, December 2002.