一种面向网络节能的VNF容量调整方法  

VNF Capacity Adjustment Method for Network Energy Saving

作　　者：朱棣 申涓[1] 李丹[1] 兰巨龙[1] ZHU Di;SHEN Juan;LI Dan;LAN Julong(Information Engineering University,Zhengzhou 450001,China)

机构地区：[1]信息工程大学,河南郑州450001

出　　处：《信息工程大学学报》2023年第2期183-189,共7页Journal of Information Engineering University

基　　金：国家重点研发计划资助项目(2020YFB1804803);国家自然科学基金资助项目(62002382)。

摘　　要：虚拟网络功能(VNF)容量调整因其能够显著提升网络服务提供过程中的资源利用率而成为研究热点,但该技术在实施时会导致网络能耗的升高。为解决该问题,提出一种面向网络节能的VNF容量调整方法。首先提出一种基于门控循环单元和注意力机制的VNF容量需求预测方法,然后根据VNF容量需求的预测结果,设计了一种基于深度强化学习的VNF容量需求映射方法完成VNF的容量调整,通过集中部署VNF实例和关闭网络中的空闲节点来降低网络能耗。实验结果表明,与经典的ORFA方法相比,所提方法提升了7.72%的资源利用率并降低了10.17%的网络能耗。Virtual network function(VNF)capacity adjustment has become a research hotspot be-cause it can significantly improve the resource utilization in the process of network service provision,but this technology will lead to an increase in network energy consumption when implemented.To solve this problem,a VNF capacity adjustment method for network energy saving is proposed.Firstly,a VNF capacity demand prediction method based on gated recurrent unit(GRU)and attention mechanism is proposed.Then,based on the predicted result of VNF capacity demand,a VNF ca-pacity demand mapping method is designed,which utilizes deep reinforcement learning(DRL)to centrally deploy VNF instances and shut down idle nodes in the network to reduce energy consump-tion while improving network resource utilization.Experimental results show that,compared with ex-isting VNF capacity adjustment methods,the proposed method improves resource utilization by at least 7.72%and reduces network energy consumption by at least 10.17%.

关 键 词：虚拟网络功能 容量调整 资源利用率 能耗 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]