Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Adaptation of MANET topology to monitor dynamic phenomena clouds


DOI: http://dx.doi.org/10.15439/2017F294

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 865872 ()

Full text

Abstract. The paper is concerned with the application of mobile ad hoc networks to phenomena clouds boundary detection and tracking. Self-organizing, coherent networks comprised of sensors and radio transceivers that maintain a continuous communication with each other and a central operator are considered. The attention is focused on the methodology for determining the temporarily optimal network topology for detecting the boundary of a cloud that can change its shape in time. We introduce several measures for assessment a quality of a network topology and propose a computing scheme for detection topology that is the optimal one at a given time. The utility and efficiency of the proposed methodology was justified through simulation experiments.


  1. M. T. Thai, R. Tiwari, R. Bose, and A. Helal, “On detection and tracking of variant phenomena clouds,” ACM Trans. Sen. Netw., vol. 10, no. 2, pp. 34:1–34:33, Jan. 2014. http://dx.doi.org/10.1145/2530525
  2. T. Facchinetti, G. Franchino, and G. Buttazzo, “A distributed coordination protocol for the connectivity maintenance in a network of mobile units,” in Sensor Technologies and Applications, 2008. SEN-SORCOMM’08. Second International Conference on. IEEE, 2008. http://dx.doi.org/10.1109/SENSORCOMM.2008.31 pp. 764–769.
  3. Z. Kan, L. Navaravong, J. M. Shea, E. L. Pasiliao, and W. E. Dixon, “Graph matching-based formation reconfiguration of networked agents with connectivity maintenance,” Control of Network Systems, IEEE Transactions on, vol. 2, no. 1, pp. 24–35, 2015. http://dx.doi.org/10.1109/TCNS.2014.2367363
  4. N. Michael, M. M. Zavlanos, V. Kumar, and G. J. Pappas, “Maintaining connectivity in mobile robot networks,” in Experimental Robotics. Springer, 2009. http://dx.doi.org/10.1007/978-3-642-00196-3-14 pp. 117–126.
  5. A. Konak, G. E. Buchert, and J. Juro, “A flocking-based approach to maintain connectivity in mobile wireless ad hoc networks,” Applied Soft Computing, vol. 13, no. 2, pp. 1284–1291, 2013. http://dx.doi.org/10.1016/j.asoc.2012.10.020
  6. M. Krzyszton and E. Niewiadomska-Szynkiewicz, “Heavy gas cloud boundary estimation and tracking using mobile sensors,” Journal of Telecommunications and Information Technology, no. 3, p. 38, 2016.
  7. E. Niewiadomska-Szynkiewicz, A. Sikora, and M. Marks, “A movement-assisted deployment of collaborating autonomous sensors for indoor and outdoor environment monitoring,” Sensors, vol. 16, no. 9, p. 1497, 2016. http://dx.doi.org/10.3390/s16091497
  8. M. Patan, Optimal sensor networks scheduling in identification of distributed parameter systems. Springer Science & Business Media, 2012, vol. 425.
  9. M. Krzysztoń, “Comparison of manet self-organization methods for boundary detection/tracking of heavy gas cloud,” in Computer Science and Information Systems (FedCSIS), 2016 Federated Conference on. IEEE, 2016. http://dx.doi.org/10.15439/2016F240 pp. 1075–1084.
  10. S. Srinivasan, S. Dattagupta, P. Kulkarni, and K. Ramamritham, “A survey of sensory data boundary estimation, covering and tracking techniques using collaborating sensors,” Pervasive and Mobile Computing, vol. 8, no. 3, pp. 358–375, 2012. http://dx.doi.org/10.1016/j.pmcj.2012.03.003
  11. K. Shanmugam, K. Subburathinam, and A. Velayuthampalayam Palanisamy, “A dynamic probabilistic based broadcasting scheme for manets,” The Scientific World Journal, vol. 2016, 2016. http://dx.doi.org/10.1155/2016/1832026
  12. M. Król, E. Schiller, F. Rousseau, and A. Duda, “Weave: Efficient geographical routing in large-scale networks.” in EWSN, 2016, pp. 89–100.
  13. R. Virrankoski and A. Savvidees, “Tasc: topology adaptive spatial clustering for sensor networks,” in Mobile Adhoc and Sensor Systems Conference, 2005. IEEE International Conference on. IEEE, 2005. http://dx.doi.org/10.1109/MAHSS.2005.1542850 pp. 10–pp.
  14. M. Zhao and W. Wang, “Analyzing topology dynamics in ad hoc networks using a smooth mobility model,” in Wireless Communications and Networking Conference, 2007. WCNC 2007. IEEE. IEEE, 2007. http://dx.doi.org/10.1109/WCNC.2007.604 pp. 3279–3284.
  15. A. Sikora, E. Niewiadomska-Szynkiewicz, and M. Krzysztoń, “Simulation of mobile wireless ad hoc networks for emergency situation awareness,” in Computer Science and Information Systems (FedCSIS), 2015 Federated Conference on. IEEE, 2015. http://dx.doi.org/10.15439/2015F52 pp. 1087–1095.
  16. D. Morgan Jr, L. K. Morris, and D. L. Ermak, “Slab: a time-dependent computer model for the dispersion of heavy gases released in the atmosphere,” Lawrence Livermore National Lab., CA (USA), Tech. Rep., 1983.
  17. E. Niewiadomska-Szynkiewicz, A. Sikora, and J. Kołodziej, “Modeling mobility in cooperative ad hoc networks,” Mobile Networks and Applications, vol. 18, no. 5, pp. 610–621, 2013. http://dx.doi.org/10.1007/s11036-013-0450-2