Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/470805
Title: Study on energy efficient clustering algorithms for wireless sensor networks
Researcher: Sathyapriya L
Guide(s): Jawahar A
Keywords: Engineering and Technology
Computer Science
Computer Science Information Systems
Wireless sensor networks
Network lifetime
Particle swarm optimization
University: Anna University
Completed Date: 2021
Abstract: Wireless sensor networks (WSNs) consist of dedicated sensors, newlinewhich monitor and record various physical and environmental conditions like newlinetemperature, pollution levels, humidity and so on. WSN is compatible with newlineseveral applications related to environmental and healthcare monitoring. The newlinesensor nodes have limited battery life and are deployed in hostile environments. newlineThe big challenge of limited battery capacity obstructs remote and inaccessible newlineareas where their use is the most favorable. Recharging or replacement of the newlinebatteries in the sensor nodes is very difficult after deployment in inaccessible newlineareas. Energy efficiency is a major concern in wireless sensor networks newlineas it is important for maintaining network operation. For extending the newlinelifetime of the network, the battery should optimally utilize it for different newlineoperations. Clustering is the most energy efficient technique for saving energy newlinein sensor networks. The requirement towards low complexity and low energy newlineconsumption motivates to design the energy efficient clustering algorithms for newlineWireless Sensor Networks.The sensor nodes groups into clusters; one sensor newlinenode is chosen as a cluster head, and communication to the sink node from newlinethe sensor nodes occurs through the cluster head (CH) node. The appropriate newlinemethod for selecting the cluster head is still lagging. For the selection newlineof energy-efficient cluster head sensor node, an energy-efficient clustering newlinealgorithm based energy centroid and energy threshold is proposed. Here each newlinecluster is designed to own 25 percent of the sensor nodes using a distance newlinecentroid algorithm. Cluster head selection is based on the energy centroid of newlineeach cluster and the energy threshold of the sensor nodes. Communication newlinebetween the sink node and cluster head uses the distance of separation as a newlineparameter for reducing energy consumption. newline
Pagination: xiv,137p.
URI: http://hdl.handle.net/10603/470805
Appears in Departments:Faculty of Information and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File39.79 kBAdobe PDFView/Open
02_prelim pages.pdf2.42 MBAdobe PDFView/Open
03_content.pdf52.11 kBAdobe PDFView/Open
04_abstract.pdf44.44 kBAdobe PDFView/Open
05_chapter 1.pdf2.4 MBAdobe PDFView/Open
06_chapter 2.pdf124.21 kBAdobe PDFView/Open
07_chapter 3.pdf4.37 MBAdobe PDFView/Open
08_chapter 4.pdf4.65 MBAdobe PDFView/Open
09_chapter 5.pdf6.93 MBAdobe PDFView/Open
10_chapter 6.pdf3.77 MBAdobe PDFView/Open
11_annexures.pdf69.95 kBAdobe PDFView/Open
80_recommendation.pdf43.79 kBAdobe PDFView/Open
Show full item record


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: