一个以参数为中心的服务发现框架,用于智能城市中的社会数字双胞胎
Farhan Amin1, Salabat Khan2, Gyu Sang Choi3
1School of Computer Science and Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.
Scientific reports
|July 22, 2025
概括
本研究介绍了社会物联网 (SIoT) 的高效服务发现算法. 它通过分析关键参数和减少网络流量来优化发现,以获得更好的智能城市应用.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 智慧城市技术 智慧城市技术
背景情况:
- 物联网 (IoT) 产生了大量的网络流量,特别是在智能城市.
- 社交物联网 (SIoT) 通过设备对设备的社交关系来增强服务.
- 现有的服务发现 (SD) 模型往往忽略了诸如时空动态和效率等关键参数.
研究的目的:
- 对社会物联网服务发现的参数进行详尽的分析.
- 使用现实世界的数据来确定这些参数的相对重要性.
- 为SIoT.提出一个高效的服务发现算法.
主要方法:
- 为SIoT服务发现进行全面的参数分析.
- 基于数据集的重要性确定参数的优先级.
- 开发一个优化的服务发现算法,重点是减少图形穿越,考虑服务类型和缓存.
主要成果:
- 确定并优先考虑关键参数,这些参数对于有效的SIoT服务发现至关重要.
- 与现有的最先进模型相比,拟议的算法显示出更高的效率和可扩展性.
- 实验验证证了拟议的服务发现方法的有效性.
结论:
- 拟议的SIoT服务发现模型显著提高了效率和可扩展性.
- 优先考虑特定参数可以在复杂的社会物联网环境中实现优化服务发现.
- 这项研究为利用SIoT的更有效的智能城市应用提供了基础.
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