ARMA-Prediction-Based Online Adaptive Dynamic Resource Allocation in Wireless Virtualized Network

ARMA-Prediction-Based Online Adaptive Dynamic Resource Allocation in Wireless Virtualized Network
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无线虚拟化网络中基于ARMA预测的在线自适应动态资源分配

DOI:
10.1109/access.2019.2940435
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发表时间:
2019-09
期刊:
影响因子:
3.9
通讯作者:
Chen Qianbin
Chen Qianbin
中科院分区:
计算机科学3区
文献类型:
--
作者:
Tang Lun;He Xiaoyu;Yang Xixi;Wei Yannan;Wang Xiao;Chen Qianbin

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无线网络虚拟化 (WNV) 为第五代 (5G) 系统提供了一种新颖的范式转变,可以更有效地利用网络资源。本文通过共同考虑无线虚拟化网络中的缓存空间和时频资源分配,首先制定优化规划来研究网络开销的最小化问题,同时满足每个虚拟网络对溢出概率的服务质量(QoS)要求。然后,考虑到虚拟网络对不同类型资源的不同需求,提出一种基于自回归移动平均(ARMA)预测方法的多时间尺度在线自适应虚拟资源分配算法来解决该问题,消除了传统方法中由于流量不确定性和信息反馈延迟而存在的不合理性。更具体地,在所提出的多时间尺度的资源调度机制中,一方面,根据长时间尺度下的ARMA预测信息制定缓存空间的预留策略。另一方面,通过大偏差原理和短时间尺度下的动态时频资源调度得出的溢出概率对虚拟网络进行排序。仿真结果表明,我们的建议可以在降低比特丢失率和提高物理资源利用率方面提供切实的收益。
Wireless network virtualization (WNV) provides a novel paradigm shift in the fifth-generation (5G) system, which enables to utilize network resources more efficiently. In this paper, by jointly considering cache space and time-frequency resource allocation in wireless virtualized networks, we first formulate an optimization programming to investigate the minimization problem of network overheads while satisfying the quality of service (QoS) requirements of each virtual network on overflow probability. Then, with diverse demands of virtual networks for different kinds of resources taken into consideration, an online adaptive virtual resource allocation algorithm with multiple time-scales based on auto regressive moving average (ARMA) prediction method is proposed to solve the formulation, which could eliminate the irrationalities existed in traditional approaches caused by the uncertainty of traffic and information feedback delay. More specifically, in the proposed resource scheduling mechanism with multiple time-scales, on the one hand, a reservation strategy of cache space is developed according to the ARMA prediction information under long time-scales. On the other hand, virtual networks are sorted by the overflow probabilities derived by the large-deviation principle and dynamic time-frequency resource scheduling under short time-scales. Simulation results reveal that our proposal can provide tangible gains in reducing the bit loss rate and improving the utilization of physical resources.
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