快速确定无线区块链网络的最佳传输速率:一个图形卷积神经网络方法
Yucong Ju1, Fei Song1, Yutao Jiao1
1College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
这项研究通过分析数据传输速率来优化无线区块链网络. 一种新的图形卷积神经网络 (GCN) 方法有效地确定最佳速率,提高吞吐量和能源效率.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 无线通信无线通信
背景情况:
- 无线区块链网络在平衡安全性,吞吐量和资源限制方面面临着挑战.
- 优化数据传输速率对于高效的网络性能至关重要.
研究的目的:
- 调查数据传输速率对各种网络拓的无线区块链性能的影响.
- 为区块链开发一个实用功能,平衡吞吐量,能源效率和老旧率.
- 提出一种有效的方法来确定无线区块链网络中的最佳数据传输速率.
主要方法:
- 收集区块链性能数据并应用曲线拟合来分析传输速率影响.
- 定义了一个包含吞吐量,能源效率和老旧率的公用事业函数.
- 开发并实施基于图形卷积神经网络 (GCN) 的方法来确定最佳速率.
主要成果:
- 该研究探讨了数据传输速率与无线区块链性能之间的关系.
- 提出了一种基于GCN的新方法,以高效准确地选择最佳数据传输速率.
- 实验结果显示,GCN衍生和最佳区块链实用之间的平均相对偏差小于0.21%.
结论:
- 提出的基于GCN的方法有效地确定了无线区块链网络的最佳数据传输速率.
- 这种方法显著改善了吞吐量,能源效率和停滞率之间的平衡.
- 这些发现有助于更高效和高性能的无线区块链网络部署.
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