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浙江大学学报(工学版)
浙江大学学报(工学版)  2019, Vol. 53 Issue (4): 785-793    DOI: 10.3785/j.issn.1008-973X.2019.04.020
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考虑控制器故障的软件定义机载网络选举算法
吕娜(),刘创(),陈柯帆,曹芳波
空军工程大学 信息与导航学院，陕西 西安 710077
Software defined airborne network election algorithm considering controller failure
Na LV(),Chuang LIU(),Ke-fan CHEN,Fang-bo CAO
School of Informational and Navigation, Air Force Engineering University, Xi’an 710077, China
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摘要：

针对机载网络环境下控制器发生不可恢复故障的问题，提出分布式的控制节点选举（DCNE）算法. 为了保证故障恢复后控制节点的性能，综合考虑邻居节点密度、平均流请求量和控制器处理能力，计算选举权值. 通过邻居节点信息的建立和维护实现选举消息的更新，提出依据节点状态传递和处理选举消息的算法. 从故障恢复后的控制域性能角度对DCNE算法进行仿真验证. 结果表明，与现有算法对比，DCNE算法在最大时延和流部署开销指标上具有更好的性能，能够较好地适用于机载网络环境.
关键词： 机载网络;  控制平面;  健壮性;  故障恢复;  控制节点选举    
Abstract:

A distributed control node election (DCNE) algorithm was proposed aiming at the problem of unrecoverable failure of the controller in the airborne network environment. The election weight was calculated by considering the neighbor node density, the average flow request amount and the controller processing capability in order to ensure the performance of the control node after the fault recovery. Then the election message was updated through the establishment and maintenance of the neighbor node information. A method of transmitting and processing election messages according to the node status was proposed. The proposed algorithm was simulated and verified from the perspective of control domain performance after fault recovery. The experimental results show that the DCNE method has better performance in terms of maximum delay and flow deployment overhead compared with the existing methods. The DCNE method can be better applied to airborne networks.
Key words: airborne network    control plane    robustness    fault recovery    controller node election
收稿日期: 2018-06-22 出版日期: 2019-03-28
CLC:  TP 302  
作者简介: 吕娜（1970—），女，教授，博士，从事航空数据链的研究. orcid.org/0000-0003-0042-9600. E-mail： lvnn2007@163.com
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引用本文:

吕娜,刘创,陈柯帆,曹芳波. 考虑控制器故障的软件定义机载网络选举算法[J]. 浙江大学学报(工学版), 2019, 53(4): 785-793.

Na LV,Chuang LIU,Ke-fan CHEN,Fang-bo CAO. Software defined airborne network election algorithm considering controller failure. Journal of ZheJiang University (Engineering Science), 2019, 53(4): 785-793.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2019.04.020    或    http://www.zjujournals.com/eng/CN/Y2019/V53/I4/785

图 1  控制器架构及控制器故障示意图
图 2  选举消息传递流程图
图 3  DCNE计算过程示意图
图 4  Controller消息发布示意图
图 5  失控节点组的拆分与合并示意图
参数 参数值
场景区域/km $200 \times 200$
失控节点个数 10~30
传输距离/km 80
节点移动模型 随机路点
节点移动速度/（m·s-1） 340
平均流请求量/（packet·ms-1） 0~2.0
表 1  单个控制器故障仿真场景参数设置
对比算法 主要描述
BF 常用于网络前期规划阶段CPP问题求解中，依据选取的性能尺度和搜索算法来确定最优情况下控制器的位置，可以作为最优解评估选举结果的有效性.
ReON 基于网络功能虚拟化技术，将网络各节点本地模块计算的网络时延和损失率信息发送给控制器进行排序，得到最优的备份控制节点.
表 2  不同故障恢复算法的描述
图 6  不同时刻下的最大时延指标示意图
图 7  不同时刻下流部署开销指标变化示意图
图 8  不同节点数量下的最大时延指标示意图
图 9  不同节点数量下的流部署开销指标示意图
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