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Volume 27 Issue 12
Dec.  2005
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Yang Shao-jun, Shi Hao-shan, Huang Rui. Study of Spatio-Temporal Information Integration Framework Based on Directed Diffusion and Mobile-Agent for Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2005, 27(12): 1994-1999.
Citation: Yang Shao-jun, Shi Hao-shan, Huang Rui. Study of Spatio-Temporal Information Integration Framework Based on Directed Diffusion and Mobile-Agent for Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2005, 27(12): 1994-1999.

Study of Spatio-Temporal Information Integration Framework Based on Directed Diffusion and Mobile-Agent for Wireless Sensor Networks

  • Received Date: 2004-06-10
  • Rev Recd Date: 2005-03-22
  • Publish Date: 2005-12-19
  • In wireless sensor networks, the nodes with valued information are usually space-time varying. This paper presents a framework for spatio-temporal information integration based on directed diffusion and mobile agent. In the framework, the bi-direction gradients are constructed by the flood of the observers interest and the sensors Object Detected Signal (ODS). ODSs are collected and analyzed to program the visiting itineraries for mobile agents during a rhythm which is a period of time triggered by an ODS message, the space-time integration is completed by mobile agents with fusion algorithms accessing the nodes on the path. A rhythm acts as a label for spatial processing, and thus the series of rhythms become a time axis for temporal integration. In addition, the relations among some key parameters of framework are discussed. Finally, results based on experiments of collaborative target recognition demonstrate the effectiveness of the proposed framework.
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  • Akyildiz I F, Su W, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: A survey[J].Computer Networks.2002, 38(4):393-422[2]Estrin D, Govindan R, Heidemann J, Kumar S. Next century challenges: scalable coordination in sensor networks. Proceedings of the 5th ACM/IEEE International Conference on Mobile Computing and Networking, Seattle, 1999: 263-270.[3]Chong C Y, Kumar S. Sensor networks: evolution, opportunities, and challenges[J].Proc. IEEE.2003, 91(8):1247-1256[4]Kumar S, Zhao F, Shepherd D. Collaborative signal and information processing in microsensor networks. IEEE Signal Processing Magazine, 2002, 19(2): 13-14.[5]Zhao F, Zhin J, Reich J. Information-driven dynamic sensor[6]collaboration for tracking applications. IEEE Signal Processing[7]Magazine, 2002, 19(2): 61-72.[8]Guibas L J. Sensing, tracking, and reasoning with relations[J].IEEE Signal Processing Magazine.2002, 19(2):73-85[9]Qi H, Xu Y. Mobile-agent-based collaborative signal and information processing in sensor networks[J].Proc. IEEE.2003, 91(8):1172-1183[10]Wu Q, Rao N S V, Barhen J, et al.. On computing mobile agent routes for data fusion in distributed sensor networks[J].IEEE Trans. on Knowledge and Data Engineering.2004, 16(6):740-753[11]Intanagonwiwat C, Govindan R, Estrin D. Directed diffusion: A scalable and robust communication paradigm for sensor networks. Proceedings of the 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking, Boston, 2000: 56-67.[12]Silva F, Heidemann J, Govindan R, Estrin D. Directed diffusion. Technical report ISI-TR-2004-586, USC/Information Sciences Institute. January 2004.[13]Dempster A P. Upper and lower probabilities induced by a multi-value mapping[J].Annals of Mathematical Statistics.1967, 38(2):325-339[14]何友, 王国宏等. 多传感器信息融合及应用. 北京: 电子工业出版社, 2001: 287-303.
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