摘要
随着物联网和移动互联网的发展,网络设备呈指数级增加,网络规模越来越大,给网络管理带来新的挑战.SNMP能够实现对大规模网络的有效管理,然而,由于被管网元数量众多,SNMP报文流量会增大主干网中的流量开销.为了降低SNMP Agent产生的Trap报文给主干网带来的通信开销,本文提出一种基于SDN的Trap报文聚合方法.该方法利用控制器下发流表规则,将Trap报文转发至聚合服务器中进行报文聚合,然后发送至管理站,从而有效减少主干网中的SNMP Trap流量.同时,为了优化传统网络结构下进行网络管理面临的额外开销大、灵活性差、管理站负载高等问题,本文设计了一种基于SDN的网络管理架构.该架构提高了网络管理灵活性,减轻了管理站负载高的问题.实验结果表明,与传统网络管理中被管网元直接将Trap报文发送给管理站的方法相比,基于SDN的Trap报文聚合方法在主干网的Trap流量减少了41.328%,大幅降低了主干网中管理流量的开销.
With the development of the IOT and mobile internet,network devices are increasing exponentially and the scale of network gets larger and larger,which brings new challenges to network management.SNMP can effectively manage large-scale networks.However,due to the large number of managed network elements,SNMP message traffic increases the traffic overhead in the backbone network.To reduce the communication overhead brought by Trap messages generated by SNMP Agent to the backbone network,we propose an SDN-based Trap message aggregation method.This method uses the controller to issue flow table rules to forward Trap messages to the aggregation server for message aggregation,and then send them to the management station,thus effectively reducing the SNMP Trap traffic in the backbone network.In order to optimize the problems of high additional overhead,poor flexibility,and high load on management station for network management under the traditional network structure,this paper designs a network management architecture based on SDN.The architecture improves network management flexibility and alleviates the high load on management stations.Experimental results show that the SDN-based Trap message aggregation method reduces the management traffic in the backbone network by 41.328%compared with the traditional network management method in which send Trap messages directly to the management stations,significantly reducing the overhead of management traffic.
作者
张子尧
吴黎兵
夏振厂
张壮壮
ZHANG Zi-yao;WU Li-bing;XIA Zhen-chang;ZHANG Zhuang-zhuang(Key Laboratory of Aerospace Information Security and Trusted Computing,Ministry of Education,School of Cyber Science and Engineering,Wuhan University,Wuhan 430072,China;School of Computer Science,Wuhan University,Wuhan 430072,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2023年第9期2059-2067,共9页
Journal of Chinese Computer Systems
基金
国家自然科学基金面上项目(61772377)资助.