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Abstract: In-network data aggregation is essential for wireless sensor networks where resources (e.g., bandwidth, energy) are limited. In a previously proposed data dissemination scheme, data is opportunistically aggregated at the intermediate nodes on a low-latency tree which may not necessarily be energy efficient. A more energy-efficient tree is a greedy tree which can be incrementally constructed by connecting each source to the closest point of the existing tree. In this paper, we propose a... (Update)
Context of citations to this paper: More
.... have also noted that such packing aggregation saves energy and bandwidth by reducing the total per transmission overhead in the net work [6]. 7. Next steps The results described in Section 5 represent an initial rather than comprehensive exploration of the performance of an...
.... a network [32] There is growing interest in data aggregation as a mechanism for making the most of precious sensor network bandwidth [13] a problem that could be easily investigated with an active sensor network. While incremental code migration has been achieved using...
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BibTeX entry: (Update)
Chalermek Intanagonwiwat, Deborah Estrin, Ramesh Govindan, and John Heidemann. Impact of network density on data aggregation in wireless sensor networks. Technical Report 01-750, University of Southern California, November 2001. http://citeseer.ist.psu.edu/article/intanagonwiwat01impact.html More
@misc{ intanagonwiwat01impact,
author = "C. Intanagonwiwat and D. Estrin and R. Govindan and J. Heidemann",
title = "Impact of network density on data aggregation in wireless sensor networks",
text = "Chalermek Intanagonwiwat, Deborah Estrin, Ramesh Govindan, and John Heidemann.
Impact of network density on data aggregation in wireless sensor networks.
Technical Report 01-750, University of Southern California, November 2001.",
year = "2001",
url = "citeseer.ist.psu.edu/article/intanagonwiwat01impact.html" }
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