Abstract
A reasonable clustering structure can make data aggregation methods run efficiently in most wireless sensor networks (WSNs). However, compared with other WSNs, the energy imbalance problem of long and linear WSNs is more serious, and the delay is higher. It is still impossible to achieve efficient data aggregation by optimizing the clustering structure. Therefore, this letter proposes a novel data aggregation tree based on a clustering structure. First, through the optimization of cluster head selection and multihop path selection, this letter proposes a long and linear nonuniform clustering structure to improve the energy balance. Furthermore, taking the minimum delay as the objective function and the number of fusion nodes and energy balance as the constraint, an aggregation node selection mechanism based on a swarm optimization algorithm is proposed to build a data aggregation tree based on a long and linear nonuniform clustering structure. The simulation results show that the proposed method can effectively reduce the delay and energy consumption and that it is suitable for long and linear WSNs.
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Acknowledgements
This work is supported by National Natural Science Foundation of China (Grant Nos. 61801330, 61825303 and 51538009), Key innovation team program of innovation talents promotion plan by MOST of China (Grant No. 2016RA4059), Shanghai Science and Technology Commission Project (Grant No. 18DZ1205706), Major Project of Special Development Fund for Shanghai Zhangjiang National Independent Innovation Demonstration Zone (Grant No. ZJ2019-ZD-003), and Fundamental Research Funds for the Central Universities (Grant No. 22120180562).
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Li, G., He, B., Wang, Z. et al. A Swarm Optimization-Enhanced Data Aggregation Tree Based on a Nonuniform Clustering Structure for Long and Linear Wireless Sensor Networks. Wireless Pers Commun 112, 2285–2295 (2020). https://doi.org/10.1007/s11277-020-07150-3
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DOI: https://doi.org/10.1007/s11277-020-07150-3