IEICE TRANSACTIONS on Information
Node Density Loss Resilient Report Generation Method for the Statistical Filtering Based Sensor Networks
Summary :
In the statistic en-route filtering, each report generation node must collect a certain number of endorsements from its neighboring nodes. However, at some point, a node may fail to collect an insufficient number of endorsements since some of its neighboring nodes may have dead batteries. This letter presents a report generation method that can enhance the generation process of sensing reports under such a situation. Simulation results show the effectiveness of the proposed method.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.9 pp.2007-2010
- Publication Date
- 2020/09/01
- Publicized
- 2020/05/29
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019EDL8163
- Type of Manuscript
- LETTER
- Category
- Information Network
Authors
Jin Myoung KIM
Sungkyunkwan University
Hae Young LEE
Cheongju University
Keyword
Latest Issue
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Jin Myoung KIM, Hae Young LEE, "Node Density Loss Resilient Report Generation Method for the Statistical Filtering Based Sensor Networks" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 9, pp. 2007-2010, September 2020, doi: 10.1587/transinf.2019EDL8163.
Abstract: In the statistic en-route filtering, each report generation node must collect a certain number of endorsements from its neighboring nodes. However, at some point, a node may fail to collect an insufficient number of endorsements since some of its neighboring nodes may have dead batteries. This letter presents a report generation method that can enhance the generation process of sensing reports under such a situation. Simulation results show the effectiveness of the proposed method.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDL8163/_p
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@ARTICLE{e103-d_9_2007,
author={Jin Myoung KIM, Hae Young LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Node Density Loss Resilient Report Generation Method for the Statistical Filtering Based Sensor Networks},
year={2020},
volume={E103-D},
number={9},
pages={2007-2010},
abstract={In the statistic en-route filtering, each report generation node must collect a certain number of endorsements from its neighboring nodes. However, at some point, a node may fail to collect an insufficient number of endorsements since some of its neighboring nodes may have dead batteries. This letter presents a report generation method that can enhance the generation process of sensing reports under such a situation. Simulation results show the effectiveness of the proposed method.},
keywords={},
doi={10.1587/transinf.2019EDL8163},
ISSN={1745-1361},
month={September},}
Copy
TY - JOUR
TI - Node Density Loss Resilient Report Generation Method for the Statistical Filtering Based Sensor Networks
T2 - IEICE TRANSACTIONS on Information
SP - 2007
EP - 2010
AU - Jin Myoung KIM
AU - Hae Young LEE
PY - 2020
DO - 10.1587/transinf.2019EDL8163
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2020
AB - In the statistic en-route filtering, each report generation node must collect a certain number of endorsements from its neighboring nodes. However, at some point, a node may fail to collect an insufficient number of endorsements since some of its neighboring nodes may have dead batteries. This letter presents a report generation method that can enhance the generation process of sensing reports under such a situation. Simulation results show the effectiveness of the proposed method.
ER -
English
