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A Hierarchical Network Management Strategy for Distributed CIIoT With Imperfect CSI | IEEE Journals & Magazine | IEEE Xplore

A Hierarchical Network Management Strategy for Distributed CIIoT With Imperfect CSI


Abstract:

In the distributed Cognitive Industrial Internet of Things (CIIoT), since industrial devices may self-organize to determine their connection and dispersion and the networ...Show More

Abstract:

In the distributed Cognitive Industrial Internet of Things (CIIoT), since industrial devices may self-organize to determine their connection and dispersion and the network may be distributed with no infrastructure, network management with self-organizing characteristics is still an unsolved and a difficult problem. To overcome this challenge, this article proposes a hierarchical network management strategy for distributed CIIoT with imperfect channel state information (CSI) considering services with different transmission delay requirements. First, we build a two-layer architecture that supports collaborative spectrum sensing and multinode spectrum sharing in a distributed CIIoT. Then, to improve the network management efficiency and reduce the number of backbone nodes (BNs) while achieving spectrum sharing for massively distributed nodes, we establish a minimum BN set mathematical model and design the simplest backbone network optimization algorithm (SBNOA). For the problem of spectrum sharing with imperfect CSI while considering the delay-sensitive industrial services, we establish a time delay model that incorporates delay-sensitive and delay-tolerant services. Based on the model, we establish a robust optimization model with multiple conditional aim-listed probability constraints that consider imperfect CSI and transform the stochastic optimization problem into a convex optimization by using the quadratic transformation method and Gaussian Q function to solve it. Simulation results show that the proposed algorithm has good performance in a distributed CIIoT.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 8, 15 April 2024)
Page(s): 13509 - 13523
Date of Publication: 30 November 2023

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