About this Journal Submit a Manuscript Table of Contents
Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 262936, 6 pages
http://dx.doi.org/10.1155/2012/262936
Research Article

Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence

Institute of System Engineering and Robotics, Bulgarian Academy of Sciences, Acad. G. Bonchev Street, Block 2, 1113 Sofia, Bulgaria

Received 10 October 2011; Accepted 27 December 2011

Academic Editor: Tzung P. Hong

Copyright © 2012 Anna Lekova. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Lindwer, D. Marculescu, T. Basten, et al., “Ambient intelligence visions and achievements: linking abstract ideas to real-world concepts,” in Proceedings of the Design Automation & Test in Europe (DATE '03), pp. 10–15, 2003.
  2. Y. Chen, A. Medina, and P. Basu, Mobility Modeling for MANETs: Generation and Understanding of Mobility Traces, ITA, 2009, https://www.usukita.org/files/paper_mobmodel_chen_09.pdf.
  3. N. Aschenbruck, C. de Waal, and P. Martini, “Distribution of nodes in disaster area scenarios and its impact on topology control strategies,” in Proceedings of the IEEE International Conference on Computer Communications (IEEE INFOCOM '08), pp. 1–6, Phoenix, Ariz, USA, April 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. A. Lekova, “Evolving fuzzy modeling for MANETs using lightweight online unsupervised learning,” International Journal of Wireless Information Networks, vol. 17, no. 1-2, pp. 34–41, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965. View at Scopus
  6. E. L. Madruga and J. J. Garcia-Luna-Aceves, “Scalable multicasting: the core-assisted mesh protocol,” Mobile Networks and Applications, vol. 6, no. 2, pp. 151–165, 2001. View at Publisher · View at Google Scholar · View at Scopus
  7. W. Su, S. J. Lee, and M. Gerla, “Mobility prediction in wireless networks,” in Proceedings of the 21st Century Military Communications Conference Proceedings (IEEE MILCOM '00), pp. 491–495, October 2000. View at Scopus
  8. S. Merugu, M. Ammar, and E. Zegura, “Routing in space and time in networks with predictable mobility,” Tech. Rep. GIT-CC-04-7, Georgia Institute of Technology, 2004.
  9. R. Hu, Z. Hu, and H. Ma, “A reliable routing algorithm based on fuzzy applicability of F sets in MANET,” in Proceedings of the 11th Pacific Rim International Symposium on Dependable Computing (PRDC '05), pp. 245–249, December 2005. View at Publisher · View at Google Scholar · View at Scopus
  10. S. Roychoudhury, P. Dutta, and B. Maiti, “Enhancing efficiency towards handling mobility uncertainty in mobile ad-hoc network (MANET),” in Proceedings of the 11th International Conference on Information Technology (ICIT '08), pp. 159–164, December 2008. View at Publisher · View at Google Scholar · View at Scopus
  11. B. L. Su, M. S. Wang, and Y. M. Huang, “Fuzzy logic weighted multi-criteria of dynamic route lifetime for reliable multicast routing in ad hoc networks,” Expert Systems with Applications, vol. 35, no. 1-2, pp. 476–484, 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. C. Wang, S. Chen, X. Yang, and Y. Gao, “Fuzzy logic-based dynamic routing management policies for mobile ad hoc networks,” in Proceedings of the Workshop on High Performance Switching and Routing (HPSR '05), pp. 341–345, May 2005. View at Scopus
  13. S. M. Mousavi, H. R. Rabiee, M. Moshref, and A. Dabirmoghaddam, “Model based adaptive mobility prediction in mobile ad-hoc networks,” in Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM '07), pp. 1713–1716, September 2007. View at Publisher · View at Google Scholar · View at Scopus
  14. N. Samaan and A. Karmouch, “A Mobility prediction architecture based on contextual knowledge and spatial conceptual maps,” IEEE Transactions on Mobile Computing, vol. 4, no. 6, pp. 537–551, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. L. Dekar and H. Kheddouci, “A cluster based mobility prediction scheme for ad hoc networks,” Ad Hoc Networks, vol. 6, no. 2, pp. 168–194, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. J. Francois, G. Leduc, and S. Martin, “Learning movement patterns in mobile networks: a generic approach,” in Proceedings of the European Wireless, pp. 128–134, Barcelona, Spain, 2004.
  17. B. Rong, G. Amoussou, Z. Dziong, M. Kadoch, and A. K. Elhakeem, “Mobility prediction aided dynamic multicast routing in MANET,” in Proceedings of the IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication, pp. 21–24, April 2005. View at Publisher · View at Google Scholar · View at Scopus
  18. E. Baburaj and V. Vasudevan, “An intelligent mesh based multicast routing algorithm for MANETs using particle swarm optimization,” International Journal of Computer Science and Network Security, vol. 8, no. 5, pp. 214–218, 2008.
  19. C. C. Shen and S. Rajagopalan, “Poster: protocol-independent packet delivery improvement service for mobile ad hoc networks,” in Proceedings of the IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, pp. 582–584, October 2004. View at Scopus
  20. E. M. Daly and M. Haahr, “Social network analysis for routing in disconnected delay-tolerant MANETs,” in Proceedings of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '07), pp. 32–40, September 2007. View at Publisher · View at Google Scholar · View at Scopus