Paper
18 November 2024 An energy-efficient routing protocol based on SP-DPC clustering in WSNs
Kaiming Su, Feng Xu
Author Affiliations +
Proceedings Volume 13398, Fourth International Conference on Optics and Communication Technology (ICOCT 2024); 133981G (2024) https://doi.org/10.1117/12.3049849
Event: Fourth International Conference on Optics and Communication Technology (ICOCT 2024), 2024, Nanjing, China
Abstract
Wireless sensor networks have extensive applications in various domains, including environmental monitoring, military reconnaissance, intelligent transportation, and healthcare. To address the shortcomings of routing protocols, particularly those related to energy consumption, we propose an Energy-efficient Routing Protocol called SDBERP (Shared Neighbor Degree and Probability Assignment Based Density Peaks Clustering Algorithm). This protocol enhances clustering efficiency by streamlining some unnecessary steps through an improved SP-DPC algorithm. For selecting cluster centers, our protocol integrates decision-making factors such as the remaining energy of the nodes and their distance from the base station. Additionally, a two-step allocation method is employed for nodes that are not chosen as cluster centers. During the cluster head selection phase, the node's energy level, its distance from the base station, and its proximity to other nodes within the cluster are considered to identify the most suitable cluster head. Our proposed protocol uses proportional clustering, which helps maintain a stable number of clusters. The routing protocol was simulated using Python, and the experimental results demonstrate its effectiveness in significantly extending the network's lifespan and minimizing energy usage.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Kaiming Su and Feng Xu "An energy-efficient routing protocol based on SP-DPC clustering in WSNs", Proc. SPIE 13398, Fourth International Conference on Optics and Communication Technology (ICOCT 2024), 133981G (18 November 2024); https://doi.org/10.1117/12.3049849
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KEYWORDS
Sensors

Head

Sensor networks

Power consumption

Data transmission

Matrices

Evolutionary algorithms

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