Abstract
Movement patterns, like flocking and converging, leading and following, are examples of high-level process knowledge derived from low-level trajectory data. Conventional techniques for the detection of movement patterns rely on centralized “omniscient” computing systems that have global access to the trajectories of mobile entities. However, in decentralized spatial information processing systems, exemplified by wireless sensor networks, individual processing units may only have access to local information about other individuals in their immediate spatial vicinity. Where the individuals in such decentralized systems are mobile, there is a need to be able to detect movement patterns using collaboration between individuals, each of which possess only partial knowledge of the global system state. This paper presents an algorithm for decentralized detection of the movement pattern flock, with applications to mobile wireless sensor networks. The algorithm’s reliability is evaluated through testing on simulated trajectories emerging from unconstrained random movement and correlated random walk.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Galton, A.: Dynamic collectives and their collective dynamics. In: Cohn, A., Mark, D.M. (eds.) COSIT 2005. LNCS, vol. 3693, pp. 300–315. Springer, Heidelberg (2005)
Gudmundsson, J., Laube, P., Wolle, T.: Movement patterns in spatio-temporal data. In: Shekhar, S., Xiong, H. (eds.) Encyclopedia of GIS, pp. 726–732. Springer, Heidelberg (2008)
Gudmundsson, J., van Kreveld, M., Speckmann, B.: Efficient detection of patterns in 2D trajectories of moving points. GeoInformatica 11(2), 195–215 (2007)
Andersson, M., Gudmundsson, J., Laube, P., Wolle, T.: Reporting leaders and followers among trajectories of moving point objects. GeoInformatica (in press)
Shirabe, T.: Correlation analysis of discrete motions. In: Raubal, M., Miller, H.J., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2006. LNCS, vol. 4197, pp. 370–382. Springer, Heidelberg (2006)
Laube, P., Imfeld, S., Weibel, R.: Discovering relative motion patterns in groups of moving point objects. International Journal of Geographical Information Science 19(6), 639–668 (2005)
Batty, M., Desyllas, J., Duxbury, E.: The discrete dynamics of small-scale spatial events: agent-based models of mobility in carnivals and street parades. International Journal of Geographical Information Science 17(7), 673–697 (2003)
Wark, T., Corke, P., Sikka, P., Klingbeil, L., Guo, Y., Crossman, C., Valencia, P., Swain, D., Bishop-Hurley, G.: Transforming agriculture through pervasive wireless sensor networks. Pervasive Computing, IEEE 6(2), 50–57 (2007)
Russell, M.: Attention all units: Dick tracy is on its way. The Sunday Age, 9 (2007)
Correll, N., Martinoli, A.: Collective inspection of regular structures using a swarm of miniature robots. In: Ang, J., Marcelo, H., Khatib, O. (eds.) Experimental Robotics IX, The 9th International Symposium on Experimental Robotics (ISER), Singapore, June 18-21. Springer Tracts in Advanced Robotics, pp. 375–385. Springer, Heidelberg (2006)
Kellerer, W., Bettstetter, C., Schwingenschlogl, C., Sties, P., Steinberg, K.E. (auto) mobile communication in a heterogeneous and converged world. IEEE Personal Communications 8(6), 41–47 (2001)
Laube, P., van Kreveld, M., Imfeld, S.: Finding remo - detecting relative motion patterns in geospatial lifelines. In: Fisher, P.F. (ed.) Developments in Spatial Data Handling. Proceedings of the 11th International Symposium on Spatial Data Handling, pp. 201–214. Springer, Berlin (2004)
Benkert, M., Gudmundsson, J., Hübner, F., Wolle, T.: Reporting flock patterns. In: Azar, Y., Erlebach, T. (eds.) ESA 2006. LNCS, vol. 4168, pp. 660–671. Springer, Heidelberg (2006)
Gudmundsson, J., van Kreveld, M.: Computing Longest Duration Flocks in Trajectory Data. In: GIS 2006: Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems, Arlington, Virginia, USA, pp. 35–42. ACM, New York (2006)
Andersson, M., Gudmundsson, J., Laube, P., Wolle, T.: Reporting leadership patterns among trajectories. In: 22th Annual ACM Symposium on Applied Computing, Seoul, Korea, pp. 3–7 (2007)
Zhao, F., Guibas, L.J.: Wireless Sensor Networks – An Information Processing Approach. Morgan Kaufmann Publishers, San Francisco (2004)
Nittel, S., Stefanidis, A., Cruz, I., Egenhofer, M.J., Goldin, D., Howard, A., Labrinidis, A., Madden, S., Voisard, A., Worboys, M.: Report from the first workshop on geo sensor networks. ACM SIGMOD Record 33(1) (2004)
Guibas, L.J.: Sensing, tracking and reasoning with relations. Signal Processing Magazine, IEEE 19(2), 73–85 (2002)
Duckham, M., Nittel, S., Worboys, M.: Monitoring dynamic spatial fields using responsive geosensor networks. In: 13th annual ACM international workshop on Geographic Information Systems, Bremen, Germany, pp. 51–60. ACM Press, New York (2005)
Werner-Allen, G., Johnson, J., Ruiz, M., Lees, J., Welsh, M.: Monitoring volcanic eruptions with a wireless sensor network. In: Second European Workshop on Wireless Sensor Networks, pp. 108–120 (2005)
Werner-Allen, G., Lorinez, K., Ruiz, M., Marcillo, O., Johnson, J., Lees, J., Welsh, M.: Deploying a wireless sensor network on an active volcano. IEEE Internet Computing 10(2), 18–25 (2006)
Grossglauser, M., Tse, D.N.C.: Mobility increases the capacity of ad hoc wireless networks. IEEE-ACM Transactions on Networking 10(4), 477–486 (2002)
Wolfson, O., Ouksel, A., Xu, B.: Resource discovery in disconnected mobile ad-hoc networks. In: Proc. International Workshop on Next Generation Geospatial Information (2003)
Wolfson, O., Xu, B., Sistla, A.P.: An economic model for resource exchange in mobile peer to peer networks. In: Proc. 16th International Conference on Scientific and Statistical Database Management (SSDBM 2004) (2004)
Wu, Y.H., Guan, L.J., Winter, S.: Peer-to-peer shared ride systems. In: Nittel, S., Labrinidis, A., Stefanidis, A. (eds.) Advances in Geosensor Networks. LNCS, vol. 4540. Springer, Berlin (2007)
Estrin, D., Govindan, R., Heidemann, J., Kumar, S.: Next century challenges: scalable coordination in sensor networks. In: MobiCom 1999: Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking, Seattle, Washington, United States, pp. 263–270. ACM, New York (1999)
Rabiner, H.W., Kulik, J., Balakrishnan, H.: Adaptive protocols for information dissemination in wireless sensor networks. In: 5th annual ACM/IEEE international conference on Mobile computing and networking, Seattle, Washington, United States, pp. 174–185. ACM, New York (1999)
Datta, S., Bhaduri, K., Giannella, C., Kargupta, H., Wolff, R.: Distributed data mining in peer-to-peer networks. IEEE Internet Computing 10(4), 18–26 (2006)
Grossglauser, M., Vetterli, M.: Locating mobile nodes with ease: learning efficient routes from encounter histories alone. IEEE/ACM Transactions on Networking 14(3), 457–469 (2006)
Estrin, D., Govindan, R., Heidemann, J.: Embedding the internet - introduction. Communications of the ACM 43(5), 38–41 (2000)
Turchin, P.: Quantitative Analysis of Movement: Measuring and Modelling Population Redistribution in Animals and Plants. Sinauer Publishers, Sunderland (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Laube, P., Duckham, M., Wolle, T. (2008). Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes. In: Cova, T.J., Miller, H.J., Beard, K., Frank, A.U., Goodchild, M.F. (eds) Geographic Information Science. GIScience 2008. Lecture Notes in Computer Science, vol 5266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87473-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-87473-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87472-0
Online ISBN: 978-3-540-87473-7
eBook Packages: Computer ScienceComputer Science (R0)