Browse > Article

Minimizing Redundant Route Nodes in USN by Integrating Spatially Weighted Parameters: Case Study for University Campus  

Kim, Jin-Taek (Fire Department, Daegu Metropolitan City Office)
Um, Jung-Sup (Department of Geography, Kyungpook National University)
Publication Information
Journal of the Korean Geographical Society / v.45, no.6, 2010 , pp. 788-805 More about this Journal
Abstract
The present USN (Ubiquitous Sensor Networks) node deployment practices have many limitations in terms of positional connectivity. The aim of this research was to minimize a redundancy of USN route nodes, by integrating spatially weighted parameters such as visibility, proximity to cell center, road density, building density and cell overlapping ratio into a comprehensive GIS database. This spatially weighted approach made it possible to reduce the number of route nodes (11) required in the study site as compared to that of the grid network method (24). The field test for RSSI (Received Signal Strength Indicator) indicates that the spatially weighted deployment could comply with the quality assurance standard for node connectivity, and that reduced route nodes do not show a significant degree of signal fluctuation for different site conditions. This study demonstrated that the spatially weighted deployment can be used to minimize a redundancy of USN route nodes in a routine manner, and the quantitative evidence removing a redundancy of USN route nodes could be utilized as major tools to ensure the strong signal in the USN, that is frequently encountered in real applications.
Keywords
USN; redundant route nodes; epatially weighted parameters;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Ogata, S., 2004, Sensors for realizing ubiquitous sensor network, Systems Control and Information, 48(11), 452-457.
2 Alshuwaikhat, H. M. and Abubakar, I., 2008, An integrated approach to achieving campus sustainability: Assessment of the current campus environmental management practices, Journal of Cleaner Production, 16(16), 1777-1785.   DOI   ScienceOn
3 Juan, L. L., Ramos, L. and Cardona, N., 1999, Application of some theoretical models for coverage prediction in macrocell urban environments, IEEE Transactions on Vehicular Technology, 48, 1463-1468.   DOI   ScienceOn
4 Sandrasegaran, K. and Prag, K., 1999, Planning point-to-multipoint radio access networks using expert systems, Expert Systems with Applications, 17, 145-166   DOI   ScienceOn
5 Weerakoon, K. G. P. K., 2002, Integration of GIS Based suitability analysis and multi-criteria evaluation for urban land use planning; Contribution from the Analytic Hierarchy Process. Proceedings of the 2002 Asian Conference on Remote Sensing, Kathmandu, Nepal.
6 Akyildiz, l. F., Wang, X., and Wang, W., 2005, Wireless mesh networks: A survey, Computer Networks, 47, 445-487.   DOI   ScienceOn
7 Breunig, M. and Baer, W., 2004, Database support for mobile route planning systems, Computers, Environment and Urban Systems, 28(6), 595-610.   DOI   ScienceOn
8 Ando, S., 2003, Sensing technologies in ubiquitous network environment: From stand-alone intelligent sensing to knowledge-shared network sensing, IEEE Transactions on Sensors and Micromachines, 123(8), 263-270.   DOI   ScienceOn
9 Akl, R. and Sawant, U., 2007, Grid-based coordinated routing in wireless sensor networks, Consumer Communications and Networking Conference, 860-864.
10 Yu, Y., Govidan, R., and Estrin, D., 2001, Geographical and energy aware routing: A recursive data dissemination protocol for wireless sensor networks, UCLA Computer Science Department Technical Report.
11 Park, H., Lim, S., Yie, I., Kim, H., Chun, K., and Lee, J., 2007, An information aggregation scheme of multi-node in ubiquitous sensor networks, Lecture Notes in Computer Science, 4743, 60-68.
12 Steve, H. L., Arie, C., and Vincent, T., 2005, Distributed geospatial infrastructure for sensor web, Computers and Geosciences, 31(2), 221-231.   DOI   ScienceOn
13 Sui, D. Z., 1992, A fuzzy GIS modeling approach for urban land evaluation, Computers, Environment and Urban Systems, 16, 101-115.   DOI   ScienceOn
14 Shim, J, P., 1989, Bibliographical research on the analytic hierarchy process(AHP), Socio-Economic Planning Sciences, 23, 161-7.   DOI   ScienceOn
15 Rui, Z., Hang, Z., and Miguel, A. L., 2006, A grid-based sink location service for large-scale wireless sensor networks, Proceedings of the 2006 International Conference on Wireless Communications and Mobile Computing, Vancouver, British Columbia, Canada.
16 Saaty, T. L., 1980, The Analytic Hierarchy Process, McGraw Hill, NY.
17 Park, J. T., 2005, Management of Ubiquitous Sensor Network, APNOMS Tutorial, Okinawa, Japan, 73p.
18 Rose, S., 2001, The Effect of Digital Elevation Model Resolution on Wave Propagation Predictions at 2.4GHz, Master Thesis, Virginia Polytechnic Institute and State University.
19 Li, C., 2006, User preferences, information transactions and location-based services: A study of urban pedestrian wayfinding, Computers, Environment and Urban Systems, 30(6). 726-740.   DOI   ScienceOn
20 Megerian, S., Koushanfar, F., Potkonjak, M., and Srivastava, M., 2005, Worst and best-case coverage in sensor networks, IEEE Transactions on Mobile Computing, 4, 84-92.   DOI
21 Ikegami, F., 1993, Theoretical prediction of propagation for future mobile communications-reviewing and looking forward, IEEE Transactions on Communications, E76-B(2), 51-57.
22 Liu, X. and Karimi, H. A., 2006, Location awareness through trajectory prediction, Computers, Environment and Urban Systems, 30(6), 741-756.   DOI   ScienceOn
23 Laia, V. S., Trueblood R. P., and Wong, B. K., 1999, Software selection: A case study of the application of the analytical hierarchical process to the selection of a multimedia authoring system, Information & Management, 36, 221-232.   DOI   ScienceOn
24 Letchner, J., Fox, D., and Lamarca, A., 2005, Large-scale localization from wireless signal strength. Proceedings of the National Conference on Artificial Intelligence.
25 Kim, K. Y., 2008, Location optimization in heterogeneous sensor network configuration for security monitoring, Journal of the Korean Geographical Society, 43(2), 220-234.   과학기술학회마을
26 Krzanowski, R. and Raper, J., 1999, Hybrid genetic algorithm for transmitter location in wireless networks, Computers, Environment and Urban Systems, 23, 359-382.   DOI   ScienceOn
27 ITU-R Assembly, 1999, Propagation effects relating to terrestrial land mobile service in the VHF and UHF bands(Question ITU-R 203/3)), ITU-R P.1406, Geneva, 1-10.
28 Jiang, B. and Yao, X., 2006, Location-based services and GIS in perspective, Computers, Environment and Urban Systems, 30(6),712-725.   DOI   ScienceOn
29 IEEE, 2003, Wireless Medium Access Control (MAC) and Physical Layer (PHY) specifications for low-rate wireless personal area networks (LR-WPANs), IEEE Std 802, 15.
30 Fritsch, D. D. K. and Volz, S., 2001, NEXUS - positioning and data management concepts for location-aware applications, Computers, Environment and Urban Systems, 25(3), 279-291.   DOI   ScienceOn
31 Dodd, M., 2001, The Validity of Using a Geographic Information System's Viewshed Function as a Predictor for the Reception of Line-of-Sight Radio Waves, Master Thesis, Virginia Polytechnic Institute and State University.
32 ESRI (Environmental System Research Institute), 2006, ArcGIS software help menu (spatial analysis toolbox).
33 Banai, R., 1993, Fuzziness in Geographic Information Systems: Contributions from the Analytic Hierarchy Process, International Journal of Geographic Information Systems, 7, 315-329.   DOI   ScienceOn
34 Chipcon Inc 2004, CC2420 IEEE 802.15.4/ 2.4GHz RF transceiver datasheet. CC2420 Product Description.
35 Casademont, J., Lopez-Aguilera, E., Paradells, J., Rojas, A., Calveras, A., Barcelo, F., and Cotrina, J., 2004, Wireless technology applied to GIS, Computers & Geosciences, 30, 671-682.   DOI   ScienceOn
36 Camp, L. J. and Tsang, R. P., 2000, Universal service in a ubiquitous digital network, Ethics and Information Technology, 2(4), 211-221.