Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Comparison of MANET self-organization methods for boundary detection/tracking of heavy gas cloud

DOI: http://dx.doi.org/10.15439/2016F240

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 1075–1084 ()

Full text

Abstract. Mobile wireless ad hoc network (MANET) becomes increasingly popular in responding to emergency situation. In this paper a possibility to support rescue team in monitoring heavy gas cloud with MANET comprised of mobile sensing devices is investigated. In the view of the current state of research, two methods for controlling mobile sensing devices during MANET self-organization are presented. The first one is based on a greedy approach whereas the second on repulsion from the estimated centroid of a cloud and other nodes. Various variants of both methods are considered and their efficiency in terms of detection quality and energy saving is evaluated with MobASim simulation software. The results are discussed and one variant is chosen as the basis for the future research.

References

  1. F. Scargiali, E. D. Rienzo, M. Ciofalo, F. Grisafi, and A. Brucato, “Heavy gas dispersion modelling over a topographically complex mesoscale: A {CFD} based approach,” Process Safety and Environmental Protection, vol. 83, no. 3, pp. 242–256, 2005. http://dx.doi.org/http://dx.doi.org/10.1205/psep.04073. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S095758200571243X
  2. R. Jones, B. Wills, and K. C., “Chlorine gas: An evolving hazardous material threat and unconventional weapon,” Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, vol. 11, no. 2, pp. 151–156, May 2010. http://dx.doi.org/10.1109/TIE.2012.2196010
  3. C. C. Yockey, B. M. Eden, and R. B. Byrd, “The McConnell missile accident. Clinical spectrum of nitrogen dioxide exposure,” JAMA, vol. 244, no. 11, pp. 1221–1223, Sep 1980.
  4. N. B. Charan, C. G. Myers, S. Lakshminarayan, and T. M. Spencer, “Pulmonary injuries associated with acute sulfur dioxide inhalation,” Am. Rev. Respir. Dis., vol. 119, no. 4, pp. 555–560, Apr 1979.
  5. P. J. Baxter, M. Kapila, and D. Mfonfu, “Lake nyos disaster, cameroon, 1986: the medical effects of large scale emission of carbon dioxide?” BMJ, vol. 298, no. 6685, pp. 1437–1441, 1989. http://dx.doi.org/10.1136/bmj.298.6685.1437
  6. G. J. Fitzgerald, “Chemical warfare and medical response during world war i,” American journal of public health, vol. 98, no. 4, p. 611, 2008. http://dx.doi.org/10.2105/AJPH.2007.11930
  7. R. Saladi, E. Smith, and A. Persaud, “Mustard: a potential agent of chemical warfare and terrorism,” Clinical and experimental dermatology, vol. 31, no. 1, pp. 1–5, 2006.
  8. M. Markiewicz, “Mathematical modeling of heavy gas atmospheric dispersion over complex and obstructed terrain,” Archives of Environmental Protection, vol. Vol. 36, no. 1, pp. 81–94, 2010.
  9. Y.-N. Lien, H.-C. Jang, and T.-C. Tsai, “A manet based emergency communication and information system for catastrophic natural disasters,” in 29th IEEE International Conference on Distributed Computing Systems Workshops, 2009. ICDCS Workshops ’09., June 2009. http://dx.doi.org/10.1109/ICDCSW.2009.72. ISSN 1545-0678 pp. 412–417.
  10. Y.-N. Lien, L.-C. Chi, and C.-C. Huang, “A multi-hop walkie-talkie-like emergency communication system for catastrophic natural disasters,” in 39th International Conference on Parallel Processing Workshops (ICPPW), 2010, Sept 2010. http://dx.doi.org/10.1109/ICPPW.2010.77. ISSN 1530-2016 pp. 527–532.
  11. M. Aloqaily, S. Otoum, and H. Mouftah, “A novel communication system for firefighters using audio/video conferencing/sub-conferencing in standalone manets,” in 5th International Conference on Computer Science and Information Technology (CSIT), 2013, March 2013. http://dx.doi.org/10.1109/CSIT.2013.6588764 pp. 89–98.
  12. J. Kim, D. Kim, S. Jung, M. Lee, K. Kim, C. Lee, J. Nah, S. Lee, J. Kim, W. Choi, and S. Yoo, “Implementation and performance evaluation of mobile ad hoc network for emergency telemedicine system in disaster areas,” in Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, Sept 2009. http://dx.doi.org/10.1109/IEMBS.2009.5333889. ISSN 1557-170X pp. 1663–1666.
  13. E. Kulla, R. Ozaki, A. Uejima, H. Shimada, K. Katayama, and N. Nishihara, “Real world emergency scenario using manet in indoor environment: Experimental data,” in Ninth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS), 2015, July 2015. http://dx.doi.org/10.1109/CISIS.2015.49 pp. 336–341.
  14. T. Aurisch and J. Tölle, “Relay placement for ad-hoc networks in crisis and emergency scenarios,” in Proceedings of the Information Systems and Technology Panel Symposium (IST-091), Bucharest, Romania, vol. 11, 2009.
  15. A. Martín-Campillo, R. Martí, S. Robles, and C. Martínez-García, “Mobile agents for critical medical information retrieving from the emergency scene,” in 7th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2009), ser. Advances in Intelligent and Soft Computing, Y. Demazeau, J. Pavón, J. Corchado, and J. Bajo, Eds. Springer Berlin Heidelberg, 2009, vol. 55, pp. 30–39. ISBN 978-3-642-00486-5. [Online]. Available: http://dx.doi.org/10.1007/978-3-642-00487-2_4
  16. R. Martí, S. Robles, A. Martín-Campillo, and J. Cucurull, “Providing early resource allocation during emergencies: The mobile triage tag,” Journal of Network and Computer Applications, vol. 32, no. 6, pp. 1167 – 1182, 2009. http://dx.doi.org/http://dx.doi.org/10.1016/j.jnca.2009.05.006. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S1084804509000769
  17. Y. Hayakawa, K. Mori, Y. Ishida, K. Tsudaka, T. Wada, H. Okada, and K. Ohtsuki, “Development of emergency rescue evacuation support system in panic-type disasters,” in Consumer Communications and Networking Conference (CCNC), 2012 IEEE, Jan 2012. http://dx.doi.org/10.1109/C-CNC.2012.6181047 pp. 52–53.
  18. T. Tsunemine, E. Kadokawa, Y. Ueda, J. Fukumoto, T. Wada, K. Ohtsuki, and H. Okada, “Emergency urgent communications for searching evacuation route in a local disaster,” in Consumer Communications and Networking Conference, 2008. CCNC 2008. 5th IEEE, Jan 2008. http://dx.doi.org/10.1109/ccnc08.2007.267 pp. 1196–1200.
  19. T. Nakamura, K. Kogo, J. Fujimura, K. Tsudaka, T. Wada, K. Ohtsuki, and H. Okada, “Development of emergency rescue evacuation support system (eress) in panic-type disasters: Disaster detection by positioning area of terminals,” in 42nd International Conference on Parallel Processing (ICPP), 2013, Oct 2013. http://dx.doi.org/10.1109/ICPP.2013.111. ISSN 0190-3918 pp. 931–936.
  20. M. Zhong and C. Cassandras, “Distributed coverage control and data collection with mobile sensor networks,” Automatic Control, IEEE Transactions on, vol. 56, no. 10, pp. 2445–2455, Oct 2011. http://dx.doi.org/10.1109/TAC.2011.2163860
  21. 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.
  22. V. Subramanian, A. Umbarkar, and A. Doboli, “Decentralized detection and tracking of emergent kinetic data for wireless grids of embedded sensors,” in Conference on Adaptive Hardware and Systems (AHS), 2012 NASA/ESA. IEEE, 2012. http://dx.doi.org/10.1109/AHS.2012.6268650 pp. 198–204.
  23. Y. Liu and M. Li, “Iso-map: Energy-efficient contour mapping in wireless sensor networks,” in 27th International Conference on Distributed Computing Systems, 2007. ICDCS ’07., June 2007. http://dx.doi.org/10.1109/ICDCS.2007.115. ISSN 1063-6927 pp. 36–36.
  24. J.-H. Kim, K.-B. Kim, C. S. Hussain, M.-W. Cui, and M.-S. Park, “Energy-efficient tracking of continuous objects in wireless sensor networks,” in Ubiquitous Intelligence and Computing. Springer, 2008, pp. 323–337.
  25. S. Duttagupta, K. Ramamritham, and P. Ramanathan, “Distributed boundary estimation using sensor networks,” in IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS), 2006, Oct 2006. http://dx.doi.org/10.1109/MOBHOC.2006.278571 pp. 316–325.
  26. H. Hong, S. Oh, J. Lee, and S.-H. Kim, “A chaining selective wakeup strategy for a robust continuous object tracking in practical wireless sensor networks,” in IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), 2013. IEEE, 2013. http://dx.doi.org/10.1109/AINA.2013.131 pp. 333–339.
  27. K. Matsuo, K. Goto, A. Kanzaki, T. Hara, and S. Nishio, “Overhearing-based efficient boundary detection in dense mobile wireless sensor networks,” in IEEE 15th International Conference on Mobile Data Management (MDM), 2014, vol. 1. IEEE, 2014. http://dx.doi.org/10.1109/MDM.2014.34 pp. 225–234.
  28. G. Keung, B. Li, Q. Zhang, and H.-D. Yang, “The target tracking in mobile sensor networks,” in Global Telecommunications Conference (GLOBECOM 2011), 2011 IEEE, Dec 2011. http://dx.doi.org/10.1109/GLO-COM.2011.6134188. ISSN 1930-529X pp. 1–5.
  29. 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
  30. J. Brink and E. Pebesma, “Plume tracking with a mobile sensor based on incomplete and imprecise information,” Transactions in GIS, vol. 18, no. 5, pp. 740–766, 2014. http://dx.doi.org/10.1111/tgis.12063
  31. T. Sun, H. Pei, Y. Pan, and C. Zhang, “Robust adaptive neural network control for environmental boundary tracking by mobile robots,” International Journal of Robust and Nonlinear Control, vol. 23, no. 2, pp. 123–136, 2013. http://dx.doi.org/10.1002/rnc.1816.
  32. Z. Jin and A. Bertozzi, “Environmental boundary tracking and estimation using multiple autonomous vehicles,” in 46th IEEE Conference on Decision and Control, 2007, Dec 2007. http://dx.doi.org/10.1109/CDC.2007.4434857. ISSN 0191-2216 pp. 4918–4923.
  33. A. Joshi, T. Ashley, Y. R. Huang, and A. L. Bertozzi, “Experimental validation of cooperative environmental boundary tracking with on-board sensors,” in American Control Conference, 2009. ACC’09. IEEE, 2009. http://dx.doi.org/10.1109/ACC.2009.5159837 pp. 2630–2635.
  34. J. Brink, “Boundary tracking and estimation of pollutant plumes with a mobile sensor in a low-density static sensor network,” Urban Climate, 2014. http://dx.doi.org/http://dx.doi.org/10.1016/j.uclim.2014.07.002. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S2212095514000492
  35. S. Susca, F. Bullo, and S. Martínez, “Monitoring environmental bound- aries with a robotic sensor network,” Control Systems Technology, IEEE Transactions on, vol. 16, no. 2, pp. 288–296, 2008. http://dx.doi.org/10.1109/TCST.2007.903395
  36. J. Clark and R. Fierro, “Mobile robotic sensors for perimeter detection and tracking,” ISA transactions, vol. 46, no. 1, pp. 3–13, 2007. http://dx.doi.org/10.1016/j.isatra.2006.08.001
  37. D. Marthaler and A. L. Bertozzi, “Collective motion algorithms for determining environmental boundaries,” Autonomous Robots, special issue on Swarming, submitted for publication, 2003.
  38. I. Triandaf and I. B. Schwartz, “A collective motion algorithm for tracking time-dependent boundaries,” Mathematics and Computers in Simulation, vol. 70, no. 4, pp. 187 – 202, 2005. http://dx.doi.org/http://dx.doi.org/10.1016/j.matcom.2005.07.001. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0378475405001850
  39. S. Srinivasan, “Contour estimation using collaborating mobile sensors,” in In DIWANS ’06: Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks. ACM, 2006. http://dx.doi.org/10.1145/1160972.1160986 pp. 73–82.
  40. M. Kemp, A. L. Bertozzi, and D. Marthaler, “Multi-uuv perimeter surveillance,” in Proceedings of, 2004. http://dx.doi.org/10.1109/AUV.2004.1431200 pp. 102–107.
  41. S. Subchan, B. A. White, A. Tsourdos, M. Shanmugavel, and R. Zbikowski, “Dubins path planning of multiple uavs for tracking contaminant cloud,” in Proceedings of the 17th World Conference on the International Federation of Automatic Control, Seoul, Korea, 2008. http://dx.doi.org/10.3182/20080706-5-KR-1001.00964 pp. 6–11.
  42. B. White, A. Tsourdos, I. Ashokaraj, S. Subchan, R. Żbikowski et al., “Contaminant cloud boundary monitoring using network of uav sensors,” Sensors Journal, IEEE, vol. 8, no. 10, pp. 1681–1692, 2008. http://dx.doi.org/10.1109/JSEN.2008.2004298
  43. A. Sinha, A. Tsourdos, and B. White, “Multi {UAV} coordination for tracking the dispersion of a contaminant cloud in an urban region,” European Journal of Control, vol. 15, no. 3–4, pp. 441 – 448, 2009. http://dx.doi.org/http://dx.doi.org/10.3166/ejc.15.441-448. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0947358009709999
  44. D. W. Casbeer, R. W. Beard, T. W. McLain, S.-M. Li, and R. K. Mehra, “Forest fire monitoring with multiple small uavs,” in American Control Conference, 2005. Proceedings of the 2005. IEEE, 2005. doi: 10.1109/ACC.2005.1470520 pp. 3530–3535.
  45. S. Srinivasan, K. Ramamritham, and P. Kulkarni, “Ace in the hole: Adaptive contour estimation using collaborating mobile sensors,” in International Conference on Information Processing in Sensor Networks, 2008. IPSN’08. IEEE, 2008. http://dx.doi.org/10.1109/IPSN.2008.38 pp. 147–158.
  46. 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
  47. A. Sikora, E. Niewiadomska-Szynkiewicz, and M. Krzyszton, “Simulation of mobile wireless ad hoc networks for emergency situation awareness,” in Federated Conference on Computer Science and Information Systems (FedCSIS), 2015. IEEE, 2015. http://dx.doi.org/10.15439/2015F52 pp. 1087–1095.