Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hierarchical Low Power Consumption Technique with Location Information
  for Sensor Networks   In the wireless sensor networks composed of battery-powered sensor nodes, one
of the main issues is how to save power consumption at each node. The usual
approach to this problem is to activate only necessary nodes (e.g., those nodes
which compose a backbone network), and to put other nodes to sleep. One such
algorithm using location information is GAF (Geographical Adaptive Fidelity),
and the GAF is enhanced to HGAF (Hierarchical Geographical Adaptive Fidelity).
In this paper, we show that we can further improve the energy efficiency of
HGAF by modifying the manner of dividing sensor-field. We also provide a
theoretical bound on this problem.

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The categories of this paper are: atom-ph
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The categories of this paper are: alg-geom
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
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The categories of this paper are: nucl-ex
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The categories of this paper are: quant-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: econ
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The categories of this paper are: dg-ga
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The categories of this paper are: q-fin
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The categories of this paper are: math-ph
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The categories of this paper are: math
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The categories of this paper are: gr-qc
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The categories of this paper are: cond-mat