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Coverage sensitivity analysis of a wireless sensor network with different sensing range models considering boundary effects
Coverage is a crucial quality of service (QoS) parameter for wireless sensor networks (WSNs), which tells how effectively the deployed network monitors a given region. Analytical models available for the coverage analysis of finite WSNs are not scalable for large networks due to boundary effects (BE...
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Main Authors: | , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Coverage is a crucial quality of service (QoS) parameter for wireless sensor networks (WSNs), which tells how effectively the deployed network monitors a given region. Analytical models available for the coverage analysis of finite WSNs are not scalable for large networks due to boundary effects (BEs). A node located near the boundary region has less effective coverage area (ECA) as compared to the node positioned in the inner region. Furthermore, wireless channel properties vary more often due to the existence of impediments and other environmental characteristics in the communication route termed as shadowing effects (SEs). Consequently, it is crucial to include BEs and SEs while investigating the coverage performance of WSNs. In this work, we analyse the k-coverage metric of a WSN spread over a circular region (CR) by considering BEs and using a binary and a log-normal sensing range model. Furthermore, we also assess the effect of various network variables viz., the number of sensor nodes, maximum sensing range, and standard deviation of SEs on the k-coverage of the WSN. Also, we compare the k-coverage outcomes obtained by considering BEs with the results obtained by ignoring BEs. It is found that both BEs and SEs have a considerable effect on the k-coverage metric of the WSNs. The simulation outcomes substantiate analytical results and match up to a great extent. |
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ISSN: | 2214-7853 2214-7853 |
DOI: | 10.1016/j.matpr.2021.08.223 |