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 | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 39.79 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.42 MB | Adobe PDF | View/Open | |
03_content.pdf | 52.11 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 44.44 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 2.4 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 124.21 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 4.37 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 4.65 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 6.93 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 3.77 MB | Adobe PDF | View/Open | |
11_annexures.pdf | 69.95 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 43.79 kB | Adobe PDF | View/Open |
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