Network Traffic Statistics Method for Resource-Constrained Industrial Project Group Scheduling under Big Data

doi:10.1155/2021/5594663

CORC > 兰州理工大学 > 兰州理工大学 > 经济管理学院

	Network Traffic Statistics Method for Resource-Constrained Industrial Project Group Scheduling under Big Data
	Huo, Zongjie 1; Zhu, Wei 2; Pei, Pei 1
刊名	WIRELESS COMMUNICATIONS & MOBILE COMPUTING
	2021-06-11
卷号	2021
ISSN号	1530-8669
DOI	10.1155/2021/5594663
英文摘要	With the advent of the Internet era, the demand for network in various fields is growing, and network applications are increasingly rich, which brings new challenges to network traffic statistics. How to carry out network traffic statistics efficiently and accurately has become the focus of research. Although the current research results are many, they are not very ideal. Based on the era background of big data and machine learning algorithm, this paper uses the ant colony algorithm to solve the typical resource-constrained project scheduling problem and finds the optimal solution of network traffic resource allocation problem. Firstly, the objective function and mathematical model of the resource-constrained project scheduling problem are established, and the ant colony algorithm is used for optimization. Then, the project scheduling problem in PSPLIB is introduced, which contains 10 tasks and 1 renewable resource. The mathematical model and ant colony algorithm are used to solve the resource-constrained project scheduling problem. Finally, the data quantity and frequency of a PCU with a busy hour IP of 112.58.14.66 are analyzed and counted. The experimental results show that the algorithm can get the unique optimal solution after the 94th generation, which shows that the parameters set in the solution method are appropriate and the optimal solution can be obtained. The schedule of each task in the optimal scheduling scheme is very compact and reasonable. The peak time of network traffic is usually between 9 : 00 and 19 : 00-21 : 00. We can reasonably schedule the network resources according to these time periods. Therefore, the network traffic statistics method based on the solution of resource constrained industrial project group scheduling problem under big data can effectively carry out network traffic statistics and trend analysis.
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
出版者	WILEY-HINDAWI
WOS记录号	WOS:000667005900001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/148836]
专题	经济管理学院
作者单位	1.Lanzhou Univ Technol, Sch Econ & Management, Lanzhou 730050, Gansu, Peoples R China; 2.Lanzhou Univ, Sch Econ, Lanzhou 730000, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Huo, Zongjie,Zhu, Wei,Pei, Pei. Network Traffic Statistics Method for Resource-Constrained Industrial Project Group Scheduling under Big Data[J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING,2021,2021.
APA	Huo, Zongjie,Zhu, Wei,&Pei, Pei.(2021).Network Traffic Statistics Method for Resource-Constrained Industrial Project Group Scheduling under Big Data.WIRELESS COMMUNICATIONS & MOBILE COMPUTING,2021.
MLA	Huo, Zongjie,et al."Network Traffic Statistics Method for Resource-Constrained Industrial Project Group Scheduling under Big Data".WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2021(2021).