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Abstrakty
Arbitrary and random motion of mobile ad hoc network nodes while communicating results in frequent topology changes and multiple disconnections of links. This dynamic environment challenges the routing of data from the source to the destination and imposes the need for prediction models to track these changes, and then determine future topology of the network. The prediction of network mobility into the future will reduce the frequency of location updates for geographical routing protocols. Moreover it will reduce route request delay and the frequency of route updates in topology based protocols. This paper proposes a predictive model called polynomial regression trajectory estimation. This model is based on the regular behavior of nodes and uses polynomial regression to allow each mobile node to estimate its future locations as a function of time. The estimated locations will be disseminated to the network so that nodes can use them to estimate the future topologies of the entire network. The efficiency of the proposed model has been evaluated by MATLAB simulation.
Słowa kluczowe
Rocznik
Tom
Strony
451--456
Opis fizyczny
Bibliogr. 25 poz., wykr.
Twórcy
autor
autor
- Centre for Real Time Information Networks (CRIN), Faculty of Engineering and Information Technology, University of Technology, Sydney (UTS), PO Box 123, Broadway NSW 2007, Australia, malhatta@eng.uts.edu.au
Bibliografia
- [1] W. Su, S. J. Lee, and M. Gerla, “Mobility prediction in wireless networks,” in 21st Century Military Communications Conference Proceedings, vol. 1, 2000, pp. 491-495.
- [2] E. D. Kaplan, Understanding GPS: principles and applications, 2nd ed. Boston: Artech House, 2006.
- [3] M. Maroti, P. Volgyesi, S. Dora, B. Kusy, A. Nadas, A. Ledeczi, G. Balogh, and K. Molnar, “Radio interferometric geolocation,” in Proceedings of the 3rd international conference on Embedded networked sensor systems, San Diego, California, USA, 2005.
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- [5] S. Basagni, I. Chlamtac, V. Syrotiuk, and B. Woodward, “A distance routing effect algorithm for mobility (DREAM),” ACM/IEEE MOBICOM, 1998.
- [6] S. Woo and S. Singh, “Scalable routing protocol for ad hoc networks,” Wireless Networks, vol. 7, pp. 513-529, 2001.
- [7] Y. B. Ko and N. H. Vaidya, “Location-aided routing (LAR) in mobile ad hoc networks,” Wireless Networks, vol. 6, pp. 307-321, 2000.
- [8] B. Karp and H. T. Kung, “GPSR: greedy perimeter stateless routing for wireless networks,” in Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, Massachusetts, United States, 2000, pp. 243-254.
- [9] H. Hurskainen, J. Raasakka, and J. Nurmi, “Specification of GNSS application for multiprocessor platform,” in International Symposium on System-on-Chip, 2008, pp. 1-6.
- [10] J. Fulton, “Global positioning system (GPS) technology an explanation of global navigation satellite system (GNSS),” Alabama Cooperative Extension System, Tech. Rep., 2009.
- [11] S. Capkun, M. Hamdi, and J. P. Hubaux, “GPS-free positioning in mobile ad-hoc networks,” in Proceedings of the 34th Annual Hawaii International Conference on System Sciences, vol. 9, 2001.
- [12] H. A. Seyin, K. Vassil, and D. Alex, “GPS-free node localization in mobile wireless sensor networks,” in Proceedings of the 5th ACM international workshop on Data engineering for wireless and mobile access, Chicago, Illinois, USA, 2006.
- [13] S. M. Das, H. Pucha, and Y. C. Hu, “Performance comparison of scalable location services for geographic ad hoc routing,” in 24th Annual Joint Conference of the IEEE Computer and Communications Societies, 2005, pp. 1228-1239.
- [14] Z. J. Haas and B. Liang, “Ad hoc mobility management with uniform quorum systems,” IEEE/ACM Transactions on Networking, vol. 7, pp. 228-240, 1999.
- [15] M. Al-hattab and J. Agbinya, “Topology prediction and convergence for networks on mobile vehicles,” in Proceedings of the International Conference on Computer and Communication Engineering, Kuala Lumpur, Malaysia, 2008.
- [16] M. Al-Hattab and J. Agbinya, “Use of street maps to aid node localization in mobile wireless networks,” in International Symposium on Parallel and Distributed Processing with Applications, 2008, pp. 471-476.
- [17] A. Agarwal and S. R. Das, “Dead reckoning in mobile ad hoc networks,” in Wireless Communications and Networking, vol. 3, 2003, pp. 1838-1843.
- [18] V. Kumar and S. R. Das, “Performance of dead reckoning-based location service for mobile ad hoc networks: Research articles,” Wireless Communications & Mobile Computing, vol. 4, pp. 189-202, 2004.
- [19] N. Meghanathan, “Location prediction based routing protocol for mobile ad hoc networks,” in Global Telecommunications Conference, 2008, pp. 1-5.
- [20] T. Liu, P. Bahl, and I. Chlamtac, “Mobility modeling, location tracking, and trajectory prediction in wireless atm networks,” Journal on Selected Areas in Communications, vol. 16, pp. 922-936, 1998.
- [21] Z. R. Zaidi and B. L. Mark, “Mobility estimation for wireless networks based on an autoregressive model,” in Global Telecommunications Conference, vol. 6, 2004, pp. 3405-3409.
- [22] Z. R. Zaidi and B. L. Mark, “Real-time mobility tracking algorithms for cellular networks based on Kalman filtering,” in IEEE Transactions on Mobile Computing, vol. 4, 2005, pp. 195-208.
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- [24] G. Welch and G. Bishop, “An introduction to the Kalman filter,” University of North Carolina at Chapel Hill, Tech. Rep., 1995.
- [25] K. Farkasa, T. Hossmann, F. Legendre, B. Plattner, and S. K. Das, “Link quality prediction in mesh networks,” Computer Communications, vol. 31, pp. 1497-1512, 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA0-0046-0035