Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/462754
Title: | Energy efficient and secured Multi hop dynamic clustering Routing protocol in wsn |
Researcher: | Irin Loretta G |
Guide(s): | Kavitha V |
Keywords: | Engineering and Technology Computer Science Computer Science Information Systems Wireless Sensor Network Cryptography Protocol Cluster |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | In the advanced growing technology, the Wireless Sensor Network (WSN) infrastructure is self-organized that performs multi-hop or single-hop communication between nodes and thereby reduces the distance covered. There are many sensors are placed in the wide region of monitoring and follow routing protocols to exchange the information to the destination. This network is interconnected by the wireless medium for the transmission on Wireless Local Area Network (WLAN). For active communication in a local area network, the protocols like IEEE 802.11 are utilized. For reliable communication, the multi-hop model has two classifications: multi-hop flat model, and clustering model. In the first type, the same information is shared by each node and leads to high energy consumption and high overhead by the nodes. In the clustering multi-hop model, energy usage, and overhead is low due to the data aggregation by the Cluster Head (CH) and sent to sink. In clustering, CH selection ensures all the nodes are nominated as CH. The selected CH should consider the load balancing, energy consumption, preservation of energy to organize the data from the nodes and forward it to Base Station (BS). Several factors that affect network performance include storage, energy consumption, computational complexity, and limited bandwidth. newlineIn the modern era of wireless technologies, the arrival of the Internet of Things (IoT) in society has improved the lives of humans and promotes the growth of society and environment, whole economics, smart city, and smart health. IoT enables process automation, performance monitoring, labor reduction, analysis, and insight. newline |
Pagination: | xix,176p. |
URI: | http://hdl.handle.net/10603/462754 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 27.68 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.08 MB | Adobe PDF | View/Open | |
03_content.pdf | 21.42 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 10.1 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 756.78 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 805.22 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 729.08 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 709.85 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.12 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 150.37 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 69.43 kB | Adobe PDF | View/Open |
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