NDLI: Short-Term Network Traffic Prediction with ACD and Particle Filter

Content Provider	IEEE Xplore Digital Library
Author	Gaoyu Zhang Duying Huang
Copyright Year	2013
Description	Author affiliation: Sch. of Inf. Manage., Shanghai Finance Univ., Shanghai, China (Gaoyu Zhang; Duying Huang)
Abstract	Network traffic prediction is hot spot in recent years' research, which is of great significance in area such as congestion control, network management and diagnostic. Network traffic is non-linear, non-stationary, and uncertain, and its uncertainty increases rapidly when making short-term traffic flow prediction. After reviewing current network traffic prediction algorithms' merits and drawbacks based on Time-Series analysis, Artificial Neural Network here, a new network traffic prediction algorithms in short-term is proposed. The time interval when detecting that network data packet pass on certain section is treated as a stochastic process. In the ARCH (autoregressive conditional heteroskedasticity) framework, stochastic process is described by a marked point process that different point processes may generate different ACD (autoregressive conditional duration) model, then ACD model can be used to complete the description of time interval when network data packet passing. Based on this model, a particle filter is applied to non-stationary motion system for short-term network traffic prediction. At last, this algorithm is applied to real data for real-evidence analysis.
Sponsorship	IEEE Syst. Man Cybern.
Starting Page	189
Ending Page	191
File Size	161284
Page Count	3
File Format	PDF
ISBN	9780769549880
DOI	10.1109/INCoS.2013.57
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Particle Filter Stochastic processes Telecommunication traffic Prediction Predictive models Prediction algorithms ACD Model Data models Particle filters Root mean square Network Traffic
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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