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6G-enabled Edge Intelligence for Ultra -Reliable Low Latency Applications:Vision and Mission

机译:支持6G的超级低延迟应用的边缘智能:愿景和使命

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The increasing demand for automation and instant solution leads the technological world towards massive applications such as the Internet of drones, Autonomous Vehicles (AVs), border surveillance, telesurgery, and Augmented Reality (AR), which requires a vast upgrade in technology with improved processing and computation capabilities. The Centralized Cloud Server (CCS) provides the facility to compute critical tasks at the central data server, but it consumes more time due to the distance between CSS and edge device. In this article, we discuss the advantages of edge computing over cloud computing to overcome latency and reliability issues in critical applications. Moreover, the idea of processing and analyzing massive applications at the edge comes up with the requirement of building intelligence at the edge to compute complex tasks within a negligible time. Edge intelligence offers intelligence at the edge to process large datasets for critical computations and to overcome storage issues. Also, the performance tolerant connectivity and low-speed rate issues with 4G and 5G can be solved using a 6G wireless network. The 6G connected edge intelligence application offers ultra-low-latency, security, and reliability mechanisms that could be helpful in COVID-19 pandemic situations. We have also discussed the demonstration of aforementioned massive application in the form of a case study on combating COVID-19 situations using 6G-based edge intelligence. The case study depicts the benefits of using 6G (latency: 10 - l100μs) over 4G (latency:< 10ms) and 5G (latency:< 5ms) communication networks. The proposed 6G-enabled scheme is compared against the traditional 4G and 5G networks to designate its efficiency in terms of communication latency and network mobility. Eventually, we then analyzed various open issues and research challenges in this emerging research area for future gains and insights.
机译:对自动化和即时解决方案的需求不断增加,导致技术世界朝着无人机,自治车辆(AVS),边境监测,遥测和增强现实(AR)等跨互联网,这需要改进处理的技术升级和计算能力。集中式云服务器(CCS)提供了在中央数据服务器上计算关键任务的工具,但由于CSS和边缘设备之间的距离,它会消耗更多的时间。在本文中,我们讨论了云计算边缘计算的优势,以克服关键应用中的延迟和可靠性问题。此外,处理和分析边缘的大规模应用的思想提出了建筑物智能在边缘的要求,以计算复杂任务在可忽略的时间内。 Edge Intelligence在边缘提供智能,以处理大型数据集以获取关键计算并克服存储问题。此外,可以使用6G无线网络解决4G和5G的性能容忍连接和低速速率问题。 6G连接的边缘情报应用程序提供超低延迟,安全性和可靠性机制,这些机制可能有助于Covid-19大流行情况。我们还讨论了使用基于6G的边缘智能对抗Covid-19情况的案例研究表明上述大规模应用的演示。案例研究描述了使用超过4g(延迟:<10ms)和5g(延迟:<5ms)通信网络的6g(潜伏期:10 - l100μs)的益处。将所提出的6G启用方案与传统的4G和5G网络进行比较,以指定其在通信延迟和网络移动方面的效率。最终,我们在这个新兴的研究领域分析了各种开放问题和研究挑战,以获得未来的收益和见解。

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