Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/459084
Title: Improved energy efficiency in wireless sensor networks using clustering based data aggregation
Researcher: Seedha Devi V
Guide(s): Ravi T
Keywords: Wireless Sensor Networks
Clustering Algorithms
Data Aggregation
University: Anna University
Completed Date: 2021
Abstract: Wireless Sensor Network (WSN) is a collection of number of sensor nodes that are of self-configuring once deployed in a random manner across the network. Various energy efficient solutions are designed for the sensor network to increase the performance of the network by overcoming the constraint like low batter power and higher energy consumption. newlineClustering algorithms provides the effective solution that improves the load balancing and scalability of the network. This algorithm considers data transmission as its effective factor to improve the energy consumption. However, the most challenging problem is the draining of sensor battery power. Hence, various attempts are considered to improve the usage of sensor energy in the network within a specific group. newlineSeveral clustering solution involve aggregation and filtering of raw data prior transmission to the destination nodes. With increase redundancy in data samples, the transmission cost and network overload is increased. On other hand, the reduction in the transmission of packets tends to reduce the congestion. Thus the consumption of energy gets reduced in the network and it leads to improved energy efficiency. newlineThe aggregation techniques is recommended in this study, since the processing cost is significantly smaller in WSNs. With increasing sensor nodes in the WSN, the challenges lead to the network lifetime increase. Hence, the researchers proposed several ideas on data aggregation and that lead to improvement in the lifetime of the sensor networks using effective clustering algorithm. newline
Pagination: xii,109p.
URI: http://hdl.handle.net/10603/459084
Appears in Departments:Faculty of Information and Communication Engineering

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02_prelim pages.pdf1.71 MBAdobe PDFView/Open
03_content.pdf189.4 kBAdobe PDFView/Open
04_abstract.pdf185.64 kBAdobe PDFView/Open
05_chapter 1.pdf443 kBAdobe PDFView/Open
06_chapter 2.pdf489.75 kBAdobe PDFView/Open
07_chapter 3.pdf609.73 kBAdobe PDFView/Open
08_chapter 4.pdf883.58 kBAdobe PDFView/Open
09_annexures.pdf164.6 kBAdobe PDFView/Open
80_recommendation.pdf155.13 kBAdobe PDFView/Open
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