Energy Efficient Data Aggregation with Dynamic Mobile Sink-Based Path Optimization in Large Scale WSNs Using Reinforcement Learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-023-10646-3.pdf
Reference25 articles.
1. Ren, Q., & Yao, G. (2020). An energy-efficient cluster head selection scheme for energy-harvesting wireless sensor networks. Sensors, 20(1), 187.
2. Ahmed, S., Khan, M. A., Ishtiaq, A., Khan, Z. A., & Ali, M. T. (2019). Energy harvesting techniques for routing issues in wireless sensor networks. International Journal of Grid and Utility Computing, 10(1), 10–21.
3. Chen, Q., Gao, H., Cai, Z., Cheng, L., & Li, J. (2018) Energy-collision aware data aggregation scheduling for energy harvesting sensor networks. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications, (pp. 117–125). IEEE.
4. Sun, Y., He, Y., Zhang, B., & Liu, X. (2011). An energy efficiency clustering routing protocol for WSNs in confined area. Mining Science and Technology (China), 21(6), 845–850.
5. Du, T., Qu, S., Liu, F., & Wang, Q. (2015). An energy efficiency semi-static routing algorithm for WSNs based on HAC clustering method. Information fusion, 21, 18–29.
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