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ABSTRACT
Information about dynamic spatial fields, such as temperature, windspeed, or the concentration of gas pollutant in the air, is important for many environmental applications. At the same time, the development of geosensor networks (wirelessly communicating, sensor-enabled, small computing devices distributed throughout a geographic environment) present new opportunities for monitoring dynamic spatial fields in much greater detail than ever before. This paper develops a new model for querying information about dynamic spatial fields using geosensor networks. In order to manage the inherent complexity of dynamic geographic phenomena, our approach is to focus on the qualitative representation of spatial entities, like regions, boundaries, and holes, and of events, like splitting, merging, appearance, and disappearance. Based on combinatorial maps, we present a qualitative model as the underlying data management paradigm for geosensor networks. This model is capable of tracking salient changes in the network in an energy-efficient way. Further, our model enables reconfiguration of the geosensor network in response to changes in the environment. We present an algorithm capable of adapting sensor network granularity according to dynamic monitoring requirements. Regions of high variability can trigger increases in the geosensor network granularity, leading to more detailed information about the dynamic field. Conversely, regions of stability can trigger a coarsening of the sensor network, leading to efficiency increases in particular with respect to power consumption and longevity of the sensor nodes. Querying of this responsive geosensor network is also considered, and the paper concludes with a review of future research directions.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
S. Ahmad and S. P. Simonovic. Spatial system dynamics: New approach for simulation of water resources systems. Journal of Computing in Civil Engineering, 18(4):331--340, 2004.
|
 |
2
|
|
| |
3
|
J. C. Chen, J. Yip, L.and Elson, H. Wang, D. Maniezzo, R. E. Hudson, K. Yao, and D. Estrin. Coherent acoustic array processing and localization on wireless sensor network. Proceedings of the IEEE, 91(8), 2003.
|
| |
4
|
|
| |
5
|
J.R. Edmonds. A combinatorial representation for polyhedral surfaces. Notices Amer. Math. Soc., 7:646, 1960.
|
| |
6
|
A. Galton. Qualitative Spatial Change. Oxford University Press, Oxford, England, 2000.
|
| |
7
|
A. Galton. Fields and objects in space, time, and space-time. Spatial Cognition and Computation, 2004. forthcoming.
|
| |
8
|
P. Grenon and B. Smith. SNAP and SPAN: Towards dynamic spatial ontology. Spatial Cognition and Computation, 4(1):69--104, 2004.
|
 |
9
|
|
| |
10
|
J. Hellerstein, W. Hong, S. Madden, and k Stanek. Beyond average: Towards sophisticated sensing with queries. In IPSN'03, 2003.
|
| |
11
|
C. Jensen. Database aspects of location-based services. In J. Schiller and A.~Voisard, editors, Location-Based Services, chapter~5, pages 115--147. Morgan Kaufmann, 2004.
|
| |
12
|
J. G. Kroes, J. G. Wesseling, and J. C. Van Dam. Integrated modelling of the soil-water-atmosphere-plant system using the model SWAP 2.0: An overview of theory and an application. Hydrological Processes, 14(11--12):1993--2002, 2000.
|
| |
13
|
D. Livingstone, J. Raper, and T. McCarthy. Integrating aerial videography and digital photography with terrain modelling: An application for coastal geomorphology. Geomorphology, 29(1--2):77--92, 1999.
|
| |
14
|
R. L. Moses, D. Krishnamurthy, and R. M. Patterson. A self-localization method forwireless sensor networks. EURASIPJournal on Applied Signal Processing, 4:348--358, 2002.
|
| |
15
|
M. A. Mostafavi and C. Gold. A global kinetic spatial data structure for marine simulation. International Journal of Geographic Information Science, 18(3), 2004.
|
| |
16
|
|
| |
17
|
R. Muetzelfeldt and M. Duckham. Dynamic spatial modeling in the Similie visual modeling environment. In P. F. Fisher and D. J. Unwin, editors, Re-presenting GIS, chapter~17, pages 244--256. John Wiley, 2005.
|
| |
18
|
S. Nittel, M. Duckham, and L. Kulik. Information dissemination in mobile ad-hoc geosensor networks. In M.J. Egenhofer, C.~Freksa, and H.J. Miller, editors, GIScience 2004, volume 3234 of Lecture Notes in Computer Science, pages 206--222. Springer, Berlin, 2004.
|
 |
19
|
S. Nittel , A. Stefanidis , I. Cruz , M. Egenhofer , D. Goldin , A. Howard , A. Labrinidis , S. Madden , A. Voisard , M. Worboys, Report from the first workshop on geo sensor networks, ACM SIGMOD Record, v.33 n.1, March 2004
[doi> 10.1145/974121.974146]
|
| |
20
|
|
| |
21
|
|
| |
22
|
J. Raper and D. Livingstone. Development of a geomorphological spatial model using object-oriented design. International Journal of Geographic information Systems, 9(4):359--184, 1995.
|
 |
23
|
|
 |
24
|
Xiaorui Wang , Guoliang Xing , Yuanfang Zhang , Chenyang Lu , Robert Pless , Christopher Gill, Integrated coverage and connectivity configuration in wireless sensor networks, Proceedings of the 1st international conference on Embedded networked sensor systems, November 05-07, 2003, Los Angeles, California, USA
[doi> 10.1145/958491.958496]
|
| |
25
|
|
|