Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/520007
Title: | Eefficient key management system for internet based light weight devices in iot |
Researcher: | Chindrella Priyadharshini T |
Guide(s): | Mohana Geetha D |
Keywords: | Cluster heads Internet of Things Wireless sensor network |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | Recently, wireless systems based on Internet of Things (IoT) have newlinereceived significant attention in several application areas. The IoT is a newlinenetwork where the physical devices, sensors, equipment, etc. can interact with newlineone another with no human intervention. Wireless sensor network (WSN) acts newlineas a vital part of the IoT, which has contributed to numerous real time newlineapplications. WSN includes a massive set of resource limited sensor nodes newlinebased on the application requirements with some base stations acting as a newlinegateway to the exterior network, like the Internet. They find it useful for newlineseveral critical as well as non-critical applications. At the same time, the newlineintegration of WSN and IoT would open new opportunities in almost all the newlineprobable domains. However, due to the varying network topologies, distinct newlineflow of traffic, and resource limited characteristics of sensor nodes, it is newlinehighly challenging to fulfill the quality of service (QoS) needs in real time newlinescenarios. Though IoT is considered to be high powered and encompasses newlineenormous resources, the sensor nodes in WSN are constrained of energy, newlinememory, battery, and processing units. newlineSince the nodes operate only through inbuilt batteries, energy newlineefficiency in the IoT assisted WSN remains a major issue, which can be newlineresolved by the use of clustering with multi-hop routing techniques. The newlineproper selection of cluster heads (CHs) and optimal route selection processes newlinecan be considered as an NP hard problem, which can be resolved by the use of newlinemetaheuristic optimization algorithms newline |
Pagination: | xv,153p. |
URI: | http://hdl.handle.net/10603/520007 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 92.56 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 2.26 MB | Adobe PDF | View/Open | |
03_contents.pdf | 112.21 kB | Adobe PDF | View/Open | |
04_abstracts.pdf | 157.4 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 1.11 MB | Adobe PDF | View/Open | |
06_chapter2.pdf | 317.9 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 251.81 kB | Adobe PDF | View/Open | |
08_chapter4.pdf | 796.93 kB | Adobe PDF | View/Open | |
09_chapter5.pdf | 931.49 kB | Adobe PDF | View/Open | |
10_chapter6.pdf | 563.03 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 267.34 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 123.05 kB | Adobe PDF | View/Open |
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