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Towards 6G Networks: Ensemble Deep Learning Empowered VNF Deployment for IoT Services

机译:迈向6G网络:集成深度学习授权为IOT服务部署VNF部署

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The prospective Internet of Things (IoT) vertical use cases demand latency perception, privacy preservation, and scalability intelligence equipped Virtual Network Function (VNF) orchestration in a dynamic context. With the massive growth of IoT connectivity, smart VNF orchestration with real-time deployment abilities is vital for the ubiquitous digital network environment. Hence, this paper collaboratively considers all the future service orchestration specifications. Moreover, we urge the necessity to go beyond the traditional service deployment framework and introduce VNF allocation at edge cloudlet small scale data-centers. Extensive simulation results manifest the applicability and potential of our proposed deep learning models with the twist of ensemble techniques for automated VNF orchestration. Additionally, our proposed ensemble deep learning aided approach inspires the employment of intelligent orchestrator to address 6G network era challenges for perpetual telecommunication research enigmas.
机译:前瞻性互联网(物联网)垂直用例需要在动态上下文中的虚拟网络功能(VNF)编排的延迟感知,隐私保存和可扩展性智能。随着物联网连接的大规模增长,具有实时部署能力的智能VNF编排对于普遍存在的数字网络环境至关重要。因此,本文协作考虑所有未来的服务编排规范。此外,我们敦促必须超越传统的服务部署框架,并在Edge Cloudlet小规模数据中心引入VNF分配。广泛的仿真结果表明了我们提出的深度学习模型的适用性和潜力,随着自动化VNF编排的集合技术的扭曲。此外,我们建议的集合深度学习辅助方法激发了智能协调仪的就业,以解决长期电信研究谜的6G网络时代挑战。

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