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Queue Stability-Based Virtual Resource Allocation for Virtualized Wireless Networks With Self-Backhauls
Author(s) -
Lun Tang,
Xixi Yang,
Xiaolin Wu,
Taiping Cui,
Qianbin Chen
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2797088
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Wireless network virtualization and self-backhauled small-cell networks are considered as two promising technologies to enable next generation wireless networks. In this paper, we propose an integrated framework for the wireless network virtualization problem under the frequency division duplexing selfbackhaul mechanism. In this context, the dynamic virtual resource allocation issue is formulated as an optimization problem, aiming at the maximization of the average total utility of the virtualized network. In the mean time, the network queue stability, the minimum average data rate for each service provider and the capacity constraint of the backhaul link are expected to be satisfied. To solve this optimization problem, the Lyapunov optimization method is adopted to overcome the challenge from the stochastic properties exhibited in the original problem, and a real-time scheduling algorithm is then investigated based on the current queue status information and the channel state information. Specifically, a Lagrange dual decomposition and an improved particle swarm optimization with random mutation are employed to ensure the effectiveness of the proposed algorithm. Simulation results are presented to verify the proposed algorithm.

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