An Energy-Aware Approach for Industrial Internet of Things in 5G Pervasive Edge Computing Environment

An Energy-Aware Approach for Industrial Internet of Things in 5G Pervasive Edge Computing Environment
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5G 普及边缘计算环境中工业物联网的能源感知方法

DOI:
10.1109/tii.2020.3007973
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发表时间:
2021-07
影响因子:
12.3
通讯作者:
Liu Xing
Liu Xing
中科院分区:
计算机科学1区
文献类型:
--
作者:
Chen Qimei;Xu Xiaoxia;Jiang Hao;Liu Xing

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在快速技术进步的推动下,工业物联网(IIoT)最近被用来增强自主工业流程。由于工业物联网将产生巨大的多样化流量,工业流程将满足频谱稀缺和按需服务需求的挑战。5G通信中的毫米波(mmW)和普适边缘计算(PEC)技术可用于处理这些要求。在这篇文章中,提出了一种新的双频框架,该框架在PEC环境中集成了mmW和微波(<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W)网络,该框架在mmW和<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W上本地执行联合资源分配和功率分配,以满足IIoT设备的特定要求。为了考虑工业物联网场景中新的突出品质因数,调度问题被表述为一个优化问题,以最大限度地减少实时环境中的工业物联网能耗。一个李雅普诺夫优化技术已被应用于目标函数具有低复杂性和快速收敛。为了解决NP难的李雅普诺夫算法,我们引入了块坐标下降法,分解的李雅普诺夫问题的两个嵌套的子问题的mmW和<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W网络。提出了一种无需初始化的半分布式方案,该方案通过<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W网络只需要很少的信息交换,而且能够获得全局最优解.数值结果表明,我们所提出的算法的有效性,并证实我们的理论分析。
Driven by the rapid technological advances, industrial Internet of Things (IIoT) has recently been embraced to enhance autonomous industrial processes. Since a huge diverse traffic would be generated by IIoT, the industrial processes would meet the challenges of spectrum scarcity and on-demand service requirements. Millimeter wave (mmW) and pervasive edge computing (PEC) technologies in 5G communication are available to deal with these requirements. In this article, a novel dual-band framework that integrates both mmW and microwave (<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W) networks in PEC environment has been proposed, which locally performs joint resource allocation and power assignment over mmW and <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W to meet IIoT devices’ specific requirements. To consider the new prominent figure of merit in IIoT scenario, the scheduling problem is formulated as an optimization problem to minimize the IIoT energy consumption in real-time environment. A Lyapunov optimization technique has been applied for the objective function with low complexity and rapid convergence. To solve the NP-hard Lyapunov algorithm, we introduce a block coordinate descent method that decompose the Lyapunov problem into two nested subproblems over the mmW and <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W networks. An initialization-free semidistributed scheme is proposed in mmW PECs, which not only requires little information exchange via the <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>W network but also achieves the global optimal solution. Numerical results are shown to demonstrate the effectiveness of our proposed algorithms and confirm our theoretical analyses.
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