Multi-objective Topology Mapping Method for Network Emulation

doi:10.16182/j.issn1004731x.joss.18-0843

Abstract

Abstract: Network emulation is an important support for the verification of new network technology, and effective mapping is the key to the emulation network topology. Considering the multiple resource requirements, a multi-objective topology mapping method (MOTM) for network emulation topology is proposed to realize the effective physical resources utilization. The method analyzes the resource requirements of nodes and links, assigns corresponding weights, converts the mapping problem into the graph partitioning problem, divides the graph by multi-level graph partitioning method, and forms a mapping strategy through remote throughput threshold optimization adjustment. The automatic deployment is implemented based on the mapping strategy. Experiments show that, compared with the Openstack mapping method and the random mapping method, MOTM reduces the load imbalance index by 66.5% and 95.5%, and the telecommunication overhead index by 69.1% and 65.2%.

Key words: network emulation, topology mapping, Openstack, multi-objective optimization

CLC Number:

TP393

Wang Xiaofeng, Chen Yang, Zhang Guangjie, Chen Jianyu. Multi-objective Topology Mapping Method for Network Emulation[J]. Journal of System Simulation, 2020, 32(8): 1436-1445.

References 17

[1]	方滨兴, 贾焰, 李爱平, 等. 网络空间靶场技术研究[J]. 信息安全学报, 2016, 1(3): 1-9.Fang Binxing, Jia Yan, Li Aiping, et al.Research on Network Space Shooting Range Technology[J]. Journal of Cyber Security, 2016, 1(3): 1-9.
[2]	Dutta A, Gnawali O.Large-scale network protocol emulation on commodity cloud[C].2014 IEEE Global Communications Conference. Austin: IEEE, 2014: 1114-1119.
[3]	Andel T R, Stewart K E, Humphries J W.Using Virtualization for Cyber Security Education and Experimentation[C]. 14th Colloquium for Information Systems Security Education. Baltimore: CISSE, 2010: 130-136.
[4]	何越. 基于云计算技术的TMSR仿真平台设计及性能分析[D]. 上海: 中国科学院大学(中国科学院上海应用物理研究所), 2018.He Yue.Design and performance analysis of TMSR simulation platform based on cloud computing technology[D]. Shanghai: University of Chinese Academy of Sciences (Shanghai Institute of Applied Physics, Chinese Academy of Sciences), 2018.
[5]	刘新波, 王布宏, 杨智显, 等. 一种基于拓扑势的虚拟网络映射算法[J]. 电子与信息学报, 2018, 40(7): 1684-1690.Liu Xinbo, Wang Buhong, Yang Zhixian, et al.A Virtual Network Mapping Algorithm Based on Topological Potential[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1684-1690.
[6]	熊文成, 王颖, 邱雪松, 等. 基于链路优先的快速协同虚拟网络映射算法[J]. 通信学报, 2015(3): 249-257.Xiong Wencheng, Wang Ying, Qiu Xuesong, et al.Fast cooperative virtual network mapping algorithm based on link priority[J]. Journal of Communications, 2015(3): 249-257.
[7]	程祥, 张忠宝, 苏森, 等. 虚拟网络映射问题研究综述[J]. 通信学报, 2011, 32(10): 143-151.Cheng Xiang, Zhang Zhongbao, Su Sen, et al.Review of virtual network mapping problems[J]. Journal of Communications, 2011, 32(10): 143-151.
[8]	DETER Team.Building apparatus for multi-resolution networking experiment using containers[R]. DeterLab, Tech.Rep. ISI-TR-683, 2011.
[9]	Yao W M, Fahmy S, Zhu J.EasyScale: Easy mapping for large-scale network security experiments[C]. 2013 IEEE Communications and Network Security (CNS): IEEE, 2014: 269-27.
[10]	Ricci R, Alfeld C, Lepreau J.A solver for the network testbed mapping problem[J]. ACM SIGCOMM Computer Communication Review (S0146-4833), 2003, 33(2): 65-81.
[11]	刘渊, 邱常伶, 王晓锋, 等. 面向多尺度融合网络仿真的拓扑映射方法研究[J]. 系统仿真学报, 2019, 31(10): 2030-2041.Liu Yuan, Qiu Changling, Wang Xiaofeng, et al.Research on Topological Mapping Method for Multiscale Fusion Network Simulation[J]. Journal of System Simulation, 2019, 31(10): 2030-2041.
[12]	Li H F, Zhou H C, Zhang H K, et al.Emustack: An openstack-based dtn network emulation platform (extended version)[J]. Mobile Information Systems (S1574-017X), 2016.
[13]	张莉莉. 基于OpenStack的虚拟机资源调度关键技术研究[D]. 北京: 北京邮电大学, 2015.Zhang Lili.Research on Key Technologies of Virtual Machine Resource Scheduling Based on OpenStack[D]. Beijing: Beijing University of Posts and Telecommunications, 2015.
[14]	蔡志平, 刘强, 吕品, 等. 虚拟网络映射模型及其优化算法[J]. 软件学报, 2012, 23(4): 864-877.Cai Zhiping, Liu Qiang, Lü Pin, et al.Virtual Network Mapping Model and Its Optimization Algorithm[J]. Journal of Software, 2012, 23(4): 864-877.
[15]	王晓锋, 方滨兴, 云晓春, 等. 并行网络蠕虫模拟中任务优化划分的研究[J]. 计算机学报, 2006, 29(8): 1367-1374.Wang Xiaofeng, Fang Binxing, Yun Xiaochun, et al.Research on task optimization partitioning in parallel network worm simulation[J]. Chinese Journal of Computers, 2006, 29(8): 1367-1374.
[16]	李斌, 王劲松, 黄玮. 一种大数据环境下的新聚类算法[J]. 计算机科学, 2015, 42(12): 247-250.Li Bin, Wang Jinsong, Huang Wei.A New Clustering Algorithm in Big Data Environment[J]. Computer Science, 2015, 42(12): 247-250.
[17]	葛文堂, 张兆心, 李斌. 基于模拟运行时间的拓扑划分评价模型[J]. 通信学报, 2013, 34(6): 122-127.Ge Wentang, Zhang Zhaoxin, Li Bin.Topological division evaluation model based on simulation running time[J]. Journal of Communications, 2013, 34(6): 122-127.