Communication Analysis of Wireless Sensor Networks with Mobility Function

The objective of this work is to investigate transmission signal patterns in static and mobile WSNs using MATLAB simulation. The simulation and subsequent analysis shows that the proposed adjustable power transmission level technique (APTL) using a ratio coefficient, is effective as a replacement to closed loop control. The results for static nodes showed effective power control, regardless of the size of the network, which reduces energy consumption in the overall network. The presented results also show the ability to pattern recognize the size of the network, with advantage of power level control. For mobile nodes, the results show an adaptive increase in power in response to increase in transmission distance. This is the adaptive power increase is represented as in an increase in the maximum power level in response to increase in transmission distance, and a reduction in the minimum power. The received signal strength indicator (RSSI), reacts in proportion to changes in transmission power, as presented by the analyzed and mathematically presented models.

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Publication Details

Published
2024-11-04
DOI
https://doi.org/10.1109/iceccme62383.2024.10796204
Citations
11
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
3.84
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article

Communication Analysis of Wireless Sensor Networks with Mobility Function

Mahmoud Zaki Iskandarani
11 citations
Energy Efficient Wireless Sensor Networks
3.84
article

Communication Analysis of Wireless Sensor Networks with Mobility Function

Mahmoud Zaki Iskandarani
article en
11 citations

Abstract

The objective of this work is to investigate transmission signal patterns in static and mobile WSNs using MATLAB simulation. The simulation and subsequent analysis shows that the proposed adjustable power transmission level technique (APTL) using a ratio coefficient, is effective as a replacement to closed loop control. The results for static nodes showed effective power control, regardless of the size of the network, which reduces energy consumption in the overall network. The presented results also show the ability to pattern recognize the size of the network, with advantage of power level control. For mobile nodes, the results show an adaptive increase in power in response to increase in transmission distance. This is the adaptive power increase is represented as in an increase in the maximum power level in response to increase in transmission distance, and a reduction in the minimum power. The received signal strength indicator (RSSI), reacts in proportion to changes in transmission power, as presented by the analyzed and mathematically presented models.

Al-Ahliyya Amman University (JO)
Affordable and clean energy
Openalex Percentile: Top 6%
Energy Efficient Wireless Sensor Networks
3.84
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