网络系统实验平台:发展现状及展望

杨林瑶; 韩双双; 王晓; 李玉珂; 王飞跃

doi:10.16383/j.aas.c180728

网络系统实验平台:发展现状及展望

doi: 10.16383/j.aas.c180728

杨林瑶^1,2,3,,
韩双双^1,2,4,,
王晓^1,2,4, ,,
李玉珂^1,2,3,,
王飞跃^1,2,5,

1.
中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京 100190
2.
青岛智能产业技术研究院青岛 266000
3.
中国科学院大学北京 100049
4.
青岛慧拓机器智能有限公司青岛 266000
5.
国防科技大学军事计算实验与平行系统技术研究中心长沙 410073

基金项目:

国家自然科学基金 61501461

国家自然科学基金 91720000

国家自然科学基金 61702519

北京市科委项目 Z181100008918007

国家自然科学基金 61533019

英特尔智能网联汽车大学合作研究中心 ICRI-IACV

详细信息

作者简介:
杨林瑶  中国科学院自动化研究所复杂系统管理与控制国家重点实验室硕士研究生.2017年获得山东大学信息科学与工程学院学士学位.主要研究方向为平行车联网大数据分析智能交通.E-mail:yanglinyao2017@ia.ac.cn

韩双双  中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员.2013年获得加拿大阿尔伯塔大学博士学位.主要研究方向为平行网络, 物联网, 智能交通, 无线通信关键技术.E-mail:shuangshuang.han@ia.ac.cn

李玉珂  中国科学院自动化研究所复杂系统管理与控制国家重点实验室博士研究生.2014年获得西安电子科技大学通信工程学士学位.主要研究方向为车联网, 物联网, 智能交通.E-mail:liyuke2014@ia.ac.cn

王飞跃  中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任, 国防科技大学军事计算实验与平行系统技术研究中心主任, 中国科学院大学中国经济与社会安全研究中心主任, 青岛智能产业技术研究院院长.主要研究方向为平行系统的方法与应用, 社会计算, 平行智能以及知识自动化.E-mail:feiyue.wang@ia.ac.cn

通讯作者:
王晓中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员.2016年获得中国科学院大学社会计算博士学位.主要研究方向为社会交通, 动态网群组织, 人工智能和社交网络分析.本文通信作者.E-mail:x.wang@ia.ac.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2018-11-05
- 录用日期: 2019-02-03
- 刊出日期: 2019-09-20

Computational Experiment Platforms for Networks: The State of the Art and Prospect

YANG Lin-Yao^{1,2,3
,},
HAN Shuang-Shuang^{1,2,4
,},
WANG Xiao^{1,2,4
, ,},
LI Yu-Ke^{1,2,3
,},
WANG Fei-Yue^{1,2,5
,}

1.
The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190
2.
Qingdao Academy of Intelligent Industries, Qingdao 266000
3.
University of Chinese Academy of Sciences, Beijing 100049
4.
Vehicle Intelligence Pioneers Inc., Qingdao 266000
5.
Research Center of Military Computational Experiments and Parallel Systems Technology, National University of Defense Technology, Changsha 410073

Funds:

National Natural Science Foundation of China 61501461

National Natural Science Foundation of China 91720000

National Natural Science Foundation of China 61702519

Beijing Municipal Science Technology Commission Z181100008918007

National Natural Science Foundation of China 61533019

Intel Collaborative Research Institute on Intelligent and Automated Connected Vehicles ICRI-IACV

More Information

Author Bio:
Master student at the the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. He received his bachelor degree in internet of things engineering from Shandong University in 2017. His research interest covers parallel internet of vehicles, big data analysis and intelligent transportation

Assistant professor at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. She received her Ph. D. degree from University of Alberta, Canada, in 2013. Her research interest covers parallel networks, internet of things, intelligent transportation system and wireless communications

Ph. D. candidate at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. She received her bachelor degree in communication engineering from Xidian University, in 2014. Her research interest covers internet of vehicles, internet of things, intelligent transportation system

State specially appointed expert and director of the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. Professor of the Research Center for Computational Experiments and Parallel Systems Technology, National University of Defense Technology. Director of China Economic and Social Security Research Center in University of Chinese Academy of Sciences. Dean of Qingdao Academy of Intelligent Industries. His research interest covers methods and applications for parallel systems, social computing, parallel intelligence, and knowledge automation

Corresponding author: WANG Xiao Associate professor at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. She received her Ph. D. degree in social computing from University of Chinese Academy of Sciences in 2016. Her research interest covers social transportation, cyber movement organizations, artificial intelligence and social network analysis. Corresponding author of this paper

摘要

摘要: 本文首先介绍了网络仿真技术的概念、特点和发展现状，在此基础上介绍了当前主流的通用型网络仿真软件的主要特点并对它们进行了对比分析和评价.为了解决现有网络架构灵活性和服务能力差的问题，我们引入了面向大数据建模、能够对网络整体状态进行预测和实时优化的平行网络架构及其计算实验平台.该平台融合虚拟的人工网络和实际网络的数据并对其进行实验分析和评估，可以发现最优的控制方案.基于平行网络计算实验方法，本文设计了针对微信朋友圈转发预测的网络优化方法，并通过实验验证了该方法可以有效提升网络的性能.
- 仿真软件 /
- 网络仿真 /
- 平行网络 /
- 计算实验 /
- 虚实交互
Abstract: In this paper, the current network experiment platforms are investigated, introduced and compared. The most popularly used simulator and its main advantages and disadvantages are demonstrated. To solve the problem of lacking flexibility and service capability of traditional network experiment platforms, based on the parallel network architecture, the corresponding computational experiment platform is proposed. The proposed platform is data-oriented, and by using the computational experiments and analysis, an optimized control strategy can be continuously updated and tracked, thus the self optimization of network systems is achieved. In the end, a computational experiment based on retweet analysis of Wechat Moments is proposed, and the effectiveness of this method is evaluated.
- Simulators /
- network simulation /
- parallel network /
- computational experiments /
- virtual-reality interaction
注释:

1) 本文责任编委王卓

HTML全文

图 1 仿真软件原理框图

Fig. 1 Schematic diagram of simulators

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图 2 NS-2双语言软件结构

Fig. 2 Two language structure of NS-2

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图 3 NS-3模块体系结构

Fig. 3 Module architecture of NS-3

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图 4 EstiNet仿真过程

Fig. 4 EstiNet simulation process

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图 5 平行网络及其计算解析

Fig. 5 Parallel network and its computational analysis

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图 6 计算实验平台系统流程图

Fig. 6 System flowchart of computational experiment platform

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图 7 传统网络与计算实验优化性能对比

Fig. 7 Performance comparison of traditional method and parallel network computational experiment

下载: 全尺寸图片幻灯片

表 1 常用仿真软件分类

Table 1 Common simulators classification

通用型	无线传感网	P2P网络	车载自组网
NS-2	SensorSim	QueryCycle	GrooveNet
NS-3	Castalia	Narses	TraNS
GlomoSim	VisualSense	3LS	NCTUns
OMNeT++	Viptos	NeuroGrid	MOVE
OPNET	Sidh	Peersim	VANET MobiSim
JiST/SWANS	Prowler	P2PSim	Veins
GTNetS	Nsrlsensorsim	SimP2	–
SSFNet	–	–	–

下载: 导出CSV

表 2 NS-2和NS-3的比较

Table 2 Comparison of NS-2 and NS-3

NS-2	NS-3
开源	开源
用户自定义模型困难	用户自定义模型容易
大量的用户贡献工具	少量的用户贡献工具
双语言编写(C++, Otcl)	单语言编写(C++)
编程能力要求高	编程能力要求适中
现有模型支持大量的协议	现有模型支持少量的协议

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表 3 JiST/SWANS与GlomoSim和NS-2的性能对比

Table 3 Comparison of JiST/SWANS, GlomoSim and NS-2

节点数	仿真器	耗时	内存消耗
500	SWANS	43 s	1 101 KB
	GlomoSim	82 s	5 759 KB
	NS-2	7136 s	5 8761 KB
5 000	SWANS	430 s	5 284 KB
5 000	GlomoSim	6191 s	27 570 KB
50 000	SWANS	4 377 s	49 262 KB
1 000 000	SWANS	–	933 MB

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表 4 仿真软件性能对比

Table 4 Performance comparison of simulators

软件名称	编程语言	平台	开源	内存消耗	速度	灵活性	可扩展性	易用性
NS-2	C++, Otcl	跨平台	开源	*	*	*	**	*
NS-3	C++	跨平台	开源	***	***	**	***	***
GlomoSim	Parsec	Linux	开源	**	**	*	***	**
QualNet	Parsec	跨平台	不开源	**	**	*	*	***
OMNeT++	C++	跨平台	开源	*	**	**	***	**
OPNET	C++	跨平台	不开源	**	*	**	*	***
J-SIM	Java	跨平台	开源	**	**	***	***	**
JiST/SWANS	Java	跨平台	开源	***	***	***	**	**
GTNetS	C++	Linux	开源	–	–	**	**	*
SSFNet	Java	跨平台	开源	–	–	*	**	**
Mininet	Python	Linux	开源	**	**	***	***	**
EstiNet	–	Linux	不开源	***	***	**	*	**

下载: 导出CSV

表 5 转发预测召回率

Table 5 Recall rate of retweet prediction

	线性分类器	决策树	SVM	随机森林
历史转发频度	5.6	71.09	89.9	71.09
浏览时间+历史转发频度	5.6	71.23	92.07	0
浏览页数/总页数+历史转发频度	5.7	71.09	3.03	0
浏览时间+浏览页数/总页数+历史转发频度	5.91	71.09	2.38	57.1

下载: 导出CSV

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