Analysis the effect of clustering and Lightweight Encryption Approaches on WSNs Lifetime

R Ahmad, EA Sundararajan… - … Conference on Electrical …, 2021 - ieeexplore.ieee.org
2021 International Conference on Electrical Engineering and …, 2021ieeexplore.ieee.org
The energy consumption and security efficiency are still main challenges in Wireless Sensor
Networks (WSNs) due to their hardware resource-constrained nature. The 6LoWPAN
protocol was developed to improve WSNs communication, security, and node management
optimization. Hence the protocol energy efficiency and security can be improved. In this
paper, we address the WSN nodes' power consumption by analyzing the Dynamic Cluster
Head (DynCH) technique, which automates the process of selecting WSN Cluster Head …
The energy consumption and security efficiency are still main challenges in Wireless Sensor Networks (WSNs) due to their hardware resource-constrained nature. The 6LoWPAN protocol was developed to improve WSNs communication, security, and node management optimization. Hence the protocol energy efficiency and security can be improved. In this paper, we address the WSN nodes' power consumption by analyzing the Dynamic Cluster Head (DynCH) technique, which automates the process of selecting WSN Cluster Head (CH) nodes based on the WSN nodes' energy and nodes' distances among each other in mobile WSN nodes. Moreover, this analysis covers the complexity of DynCH in different environments to prove its efficiency compared to the steady CH mechanism. In addition, we present the performance analysis of different lightweight systematic block encryption algorithms along with DynCH scheme on WSNs lifetime. In particular, Speck128, FlexenTech, Tiny Encryption Algorithm (TEA), and Advanced Encryption Standard (AES) algorithms are used in order to determine the amount of energy consumed by the sensor nodes and their effect on the network lifetime. The Cooja simulator is used to evaluate our analysis. Finally, the outcome of the analysis has showed that DynCH improves the wireless network lifetime by 45% compared to steady clustering approach. Moreover, the analysis also shows that, Speck128 consumed 26%, FlexenTech consumed 52%, TEA consumed 65%, and AES consumed 78% of wireless network lifetime compared to unsecure wireless networks communication, respectively.
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