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Sensor Selection Without Inter-Sensor Communication Based on Observed Sensor Data.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Sensor Selection Without Inter-Sensor Communication Based on Observed Sensor Data./
作者:
Fang, Xubin.
面頁冊數:
1 online resource (36 pages)
附註:
Source: Masters Abstracts International, Volume: 84-11.
Contained By:
Masters Abstracts International84-11.
標題:
Acoustics. -
電子資源:
click for full text (PQDT)
ISBN:
9798379559069
Sensor Selection Without Inter-Sensor Communication Based on Observed Sensor Data.
Fang, Xubin.
Sensor Selection Without Inter-Sensor Communication Based on Observed Sensor Data.
- 1 online resource (36 pages)
Source: Masters Abstracts International, Volume: 84-11.
Thesis (M.S.)--Lehigh University, 2023.
Includes bibliographical references
Reducing the number of transmissions in a wireless sensor network (WSN) to improve its energy efficiency has always been of great interest. We consider a new approach where only a fixed number of sensors will send data to the fusion center. We provide proofs and numerical results on the optimality of this approach in the case of selecting one out of two sensors. We also demonstrate numerically, the significant gains of this approach in the case of selecting 1 out of N sensors when compared to random selection, in terms of the perspective of the accuracy of decision making. We also show the performance of an approach for selecting m out of N sensors.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9798379559069Subjects--Topical Terms:
670692
Acoustics.
Subjects--Index Terms:
Energy efficiencyIndex Terms--Genre/Form:
554714
Electronic books.
Sensor Selection Without Inter-Sensor Communication Based on Observed Sensor Data.
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Advisor: Blum, Rick;Xiao, Chengshan.
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Includes bibliographical references
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Reducing the number of transmissions in a wireless sensor network (WSN) to improve its energy efficiency has always been of great interest. We consider a new approach where only a fixed number of sensors will send data to the fusion center. We provide proofs and numerical results on the optimality of this approach in the case of selecting one out of two sensors. We also demonstrate numerically, the significant gains of this approach in the case of selecting 1 out of N sensors when compared to random selection, in terms of the perspective of the accuracy of decision making. We also show the performance of an approach for selecting m out of N sensors.
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