Crisis management using spatial query processing in wireless sensor networks
Subject Areas : Wireless Networkmohammad shakeri 1 * , seyyed majid mazinani 2
1 - Neyshabur Branch, Islamic Azad university
2 - Imam Reza International University
Keywords: Wireless sensor network , query processing , spatial query , crisis management , image processing,
Abstract :
Natural disasters are an inevitable part of the world that we inhabit. Human casualties and financial losses are concomitants of these natural disasters. However, by an efficient crisis management program, we can minimize their physical and social damages. The real challenge in crisis management is the inability to timely receive the information from the stricken areas. Technology has come to the aid of crisis management programs to help find an answer to the problem. One of these technologies is wireless sensor network. With recent advances in this field, sensor nodes can independently respond to the queries from the users. This has transformed the processing of the queries into one of the most useful chapters in sensor networks. Without requiring any infrastructure, the sensor network can easily be deployed in the stricken area. And with the help of spatial query processing, it can easily provide managers with the latest information. The main problem, however, is the irregular shape of the area. Since these areas require many points to present them, the transmission of the coordinates by sensor nodes necessitates an increase in the number of data packet transmissions in the sensor network. The high number of packets considerably increases energy consumption. In related previous works, to solve this problem, line simplification algorithm s, such as Ramer-Douglas-Peucker (RDP), were used. These algorithms could lessen energy consumption by reducing the number of points in the shape of the area. In this article, we present a new algorithm to simplify packet shapes which can reduce more points with more accuracy. This results in decreasing the number of transmitted packets in the network, the concomitant reduction of energy consumption, and, finally, increasing network lifetime. Our proposed method was implemented in different scenarios and could on average reduce network’s energy consumption by 72.3%, while it caused only 4.5% carelessness which, when compared to previous methods, showed a far better performance.
[1] J. Löffler, J. Schon, V. Hernandez-Ernst, J. Pottebaum, and R. Koch, "Intelligent use of geospatial information for emergency operation management," in Proceedings of the fourth international conference on information systems for crisis management, ISCRAM, 2007.
[2] A. Soheili, V. Kalogeraki, and D. Gunopulos, "Spatial queries in sensor networks," in Proceedings of the 13th annual ACM international workshop on Geographic information systems, 2005, pp. 61-70.
[3] M. Careem, C. De Silva, R. De Silva, L. Raschid, and S. Weerawarana, "Demonstration of Sahana: free and open source disaster management," in Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains, 2007, pp. 266-267.
[4] P. K. Chitumalla, D. Harris, B. Thuraisingham, and L. Khan, "Emergency response applications: dynamic plume modeling and real-time routing," IEEE Internet Computing, vol. 12, pp. 38-44, 2008.
[5] M. A. M. Vieira, C. N. Coelho, D. da Silva, and J. M. da Mata, "Survey on wireless sensor network devices," in Emerging Technologies and Factory Automation, 2003. Proceedings. ETFA'03. IEEE Conference, 2003, pp. 537-544.
[6] J. Yick, B. Mukherjee, and D. Ghosal, "Wireless sensor network survey," Computer Networks, vol. 52, pp. 2292-2330, 2008.
[7] J. Zheng and A. Jamalipour, Wireless sensor networks: a networking perspective: John Wiley & Sons, 2009.
[8] S. R. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "TinyDB: an acquisitional query processing system for sensor networks," ACM Transactions on database systems (TODS), vol. 30, pp. 122-173, 2005.
[9] Z. Can and M. Demirbas, "A survey on in-network querying and tracking services for wireless sensor networks," Ad Hoc Networks, vol. 11, pp. 596-610, 2013.
[10]J. Gehrke and S. Madden, "Query processing in sensor networks," IEEE Pervasive Computing, vol. 3, pp. 46-55, 2004.
[11]A. Coman, M. A. Nascimento, and J. Sander, "A framework for spatio-temporal query processing over wireless sensor networks," in Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004, 2004, pp. 104-110.
[12]Google map - a desktop web mapping service. Available: https://maps.google.com
[13]W. R. Tobler, "AN EXPERIMENT IN THE COMPUTER GENERALIZATION OF MAPS," DTIC Document1964.
[14]A. H. Robinson, J. Morrison, P. C. Muehrcke, A. Kimerling, and S. Guptill, "Elements of cartography, john wiley&sons," Inc., New York, USA, 1995.
[15]P. S. Heckbert and M. Garland, "Survey of polygonal surface simplification algorithms," DTIC Document1997.
[16]D. H. Douglas and T. K. Peucker, "Algorithms for the reduction of the number of points required to represent a digitized line or its caricature," Cartographica: The International Journal for Geographic Information and Geovisualization, vol. 10, pp. 112-122, 1973.
[17]U. Ramer, "An iterative procedure for the polygonal approximation of plane curves," Computer graphics and image processing, vol. 1, pp. 244-256, 1972.
[18]T. Gökgöz, A. Sen, A. Memduhoglu, and M. Hacar, "A New Algorithm for Cartographic Simplification of Streams and Lakes Using Deviation Angles and Error Bands," ISPRS International Journal of Geo-Information, vol. 4, pp. 2185-2204, 2015.
[19]P. Chandrasekara, T. Mahaulpatha, D. Thathsara, I. Koswatta, and N. Fernando, "Landmarks based route planning and linear path generation for mobile navigation applications," Spatial Information Research, pp. 1-11, 2016.
[20]M. Lucena, J. M. Fuertes, A. L. Martinez-Carrillo, A. Ruiz, and F. Carrascosa, "Efficient classification of Iberian ceramics using simplified curves," Journal of Cultural Heritage, vol. 19, pp. 538-543, 2016.
[21]A. Jelinek, L. Zalud, and T. Jilek, "Fast total least squares vectorization," Journal of Real-Time Image Processing, pp. 1-17, 2016.
[22]R. I. da Silva, D. F. Macedo, and J. M. S. Nogueira, "Duty cycle aware spatial query processing in wireless sensor networks," Computer Communications, vol. 36, pp. 149-161, 2013.
[23]W. Li, Y. Li, P. Yu, J. Gong, and S. Shen, "The Trace Model: A model for simulation of the tracing process during evacuations in complex route environments," Simulation Modelling Practice and Theory, vol. 60, pp. 108-121, 2016.
[24]R. I. da Silva, V. D. D. Almeida, A. M. Poersch, and J. M. S. Nogueira, "Spatial query processing in wireless sensor network for disaster management," in 2009 2nd IFIP Wireless Days (WD), 2009, pp. 1-5.
[25]N. Fernández-García, L. D.-M. Martínez, A. Carmona-Poyato, F. Madrid-Cuevas, and R. Medina-Carnicer, "A new thresholding approach for automatic generation of polygonal approximations," Journal of Visual Communication and Image Representation, vol. 35, pp. 155-168, 2016.
[26]R. I. Da Silva, D. F. Macedo, and J. M. S. Nogueira, "Spatial query processing in wireless sensor networks–A survey," Information Fusion, vol. 15, pp. 32-43, 2014.
[27]"MATLAB - Simulink-Mathematical Software."