Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/311511
Title: Efficient data collection in wireless sensor networks using compressive sensing and clustering
Researcher: Lakshminarayanan R
Guide(s): Rajendran P
Keywords: Engineering and Technology
Computer Science
Computer Science Information Systems
clustering
sensing
University: Anna University
Completed Date: 2019
Abstract: Wireless sensor networks are low cost, small multifunctional sensors and low energy networks, which are deployed densely for tracking objects, environmental monitoring or controlling the operations in industries. Due to its specific challenges and impending wide applications, the wireless sensor networks have attracted many researchers in the recent times. The crucial challenge in wireless sensor networks includes its stability and energy efficiency, since the capacity of sensor node batteries are limited and hence the replacements of such batteries are difficult. To improve the capacity of sensor node batteries and to reduce the consumption of energy in network, the idea of Compressive Sensing (CS) is used in wireless sensor networks. The compressive sensing is a new sampling theory, where, the sparse signals achieves lesser sampling rate and creates a precise reconstruction of signals through lesser linear measurements. The Compressive Sensing theory is combined with wireless sensor networks to reduce the total data transmitted. It reduces well the consumption of energy in wireless sensor network, possibly increases the lifetime of network. In order to achieve the above objective, we propose two different methods that includes: Tree Cluster Data Gathering Compressive Sensing Algorithm (TCDGCSA) and Tree Cluster Adaptive Amoeba Blockwise Compressive Sensing Algorithm (TCAABCSA). newline
Pagination: xv, 117p.
URI: http://hdl.handle.net/10603/311511
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File23.51 kBAdobe PDFView/Open
02_certificates.pdf774.03 kBAdobe PDFView/Open
03_abstracts.pdf106.39 kBAdobe PDFView/Open
04_acknowledgements.pdf103.92 kBAdobe PDFView/Open
05_contents.pdf117.1 kBAdobe PDFView/Open
06_listofabbreviations.pdf222.71 kBAdobe PDFView/Open
07_chapter1.pdf613.5 kBAdobe PDFView/Open
08_chapter2.pdf269.07 kBAdobe PDFView/Open
09_chapter3.pdf772.89 kBAdobe PDFView/Open
10_chapter4.pdf598.8 kBAdobe PDFView/Open
11_chapter5.pdf579.72 kBAdobe PDFView/Open
12_conclusion.pdf250.86 kBAdobe PDFView/Open
13_references.pdf389.37 kBAdobe PDFView/Open
14_listofpublications.pdf227.43 kBAdobe PDFView/Open
80_recommendation.pdf183.94 kBAdobe PDFView/Open


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