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6G中的网络切片:智能城市物联网的战略框架。

Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities.

作者信息

Alwakeel Ahmed M, Alnaim Abdulrahman K

机构信息

Faculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia.

College of Business Administration, King Faisal University, Al Ahsa 31982, Saudi Arabia.

出版信息

Sensors (Basel). 2024 Jun 30;24(13):4254. doi: 10.3390/s24134254.

DOI:10.3390/s24134254
PMID:39001032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11243923/
Abstract

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in smart cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G smart cities' IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low round-trip time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

摘要

6G通信技术的出现给智慧城市中的物联网(IoT)带来了机遇和挑战。在本文中,我们介绍了一种先进的网络切片框架,旨在满足6G智慧城市物联网部署的复杂需求。该框架的开发遵循详细的方法,包括需求分析、指标制定、约束规范、目标设定、数学建模、配置优化、性能评估、参数调整以及最终设计的验证。我们的评估证明了该框架的高效性,其表现为低往返时间(RTT)、最小的数据包丢失、更高的可用性和增强的吞吐量。值得注意的是,该框架具有有效的扩展性,能够同时管理多个连接而不影响资源效率。通过诸如256位加密和高认证成功率等强大功能实现了增强的安全性。讨论详细阐述了这些发现,强调了该框架令人印象深刻的性能、可扩展性和安全能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/c1d45536fa9a/sensors-24-04254-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/4dbea9de010a/sensors-24-04254-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/3d09284d0745/sensors-24-04254-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/46825016a3b9/sensors-24-04254-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/f2743fe2ca8c/sensors-24-04254-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/ae28939da98c/sensors-24-04254-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/36eed94e8e46/sensors-24-04254-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/c1d45536fa9a/sensors-24-04254-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/4dbea9de010a/sensors-24-04254-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/3d09284d0745/sensors-24-04254-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/46825016a3b9/sensors-24-04254-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/f2743fe2ca8c/sensors-24-04254-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/ae28939da98c/sensors-24-04254-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/36eed94e8e46/sensors-24-04254-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f487/11243923/c1d45536fa9a/sensors-24-04254-g007.jpg

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3
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Sensors (Basel). 2023 Aug 30;23(17):7528. doi: 10.3390/s23177528.