Agglomerative Clustering of Network Traffic Based on Various Approaches to Determining the Distance Matrix

Deart, Vladimir; Mankov, Vladimir; Krasnova, Irina A.

doi:10.23919/fruct50888.2021.9347616

2021 28th Conference of Open Innovations Association (FRUCT) 2021

DOI: 10.23919/fruct50888.2021.9347616

|View full text |Cite

Agglomerative Clustering of Network Traffic Based on Various Approaches to Determining the Distance Matrix

Vladimir Deart

Vladimir Mankov²,

Irina A. Krasnova

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2022

Publication Types

Select...

Article2

Relationship

Self Cite1

Independent1

Authors

Journals

Cited by 2 publications

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Software Methodology for Estimating the Efficiency of the Hardware Composition of Deep Packet Inspection System Using the Modernized Hooke ‒ Jeeves Method

Fitsov

2021

Tr. učebn. zaved. svâzi

View full text Add to dashboard Cite

Deep packet inspection systems on communication networks are used to identify the application generating a specific traffic flow. The issues related to modeling and design of deep packet inspection systems remain poorly understood. In this paper, a software technique for evaluating the effectiveness of the hardware composition of the servers of the deep packet inspection system is presented, using a mathematical model of such a system and software search methods. The description of the program search by the maximum element method and the Hook - Jeeves method is given. A modernization of the Hook-Jeeves method for a monotonically decreasing function is proposed. Comparison of the methods by the number of search steps is performed.

show abstract

Software Methodology for Estimating the Efficiency of the Hardware Composition of Deep Packet Inspection System Using the Modernized Hooke ‒ Jeeves Method

Fitsov

2021

Tr. učebn. zaved. svâzi

View full text Add to dashboard Cite

show abstract

Traffic Flows Forecasting Based on Machine Learning

Deart

Mankov²,

Krasnova

2022

International Journal of Embedded and Real-Time Communication Systems

Self Cite

View full text Add to dashboard Cite

The article aims to develop a model for forecasting the characteristics of traffic flows in real-time based on the classification of applications using machine learning methods to ensure the quality of service. It is shown that the model can forecast the mean rate and frequency of packet arrival for the entire flow of each class separately. The prediction is based on information about the previous flows of this class and the first 15 packets of the active flow. Thus, the Random Forest Regression method reduces the prediction error by approximately 1.5 times compared to the standard mean estimate for transmitted packets issued at the switch interface.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Agglomerative Clustering of Network Traffic Based on Various Approaches to Determining the Distance Matrix

Cited by 2 publications

References 5 publications

Software Methodology for Estimating the Efficiency of the Hardware Composition of Deep Packet Inspection System Using the Modernized Hooke ‒ Jeeves Method

Software Methodology for Estimating the Efficiency of the Hardware Composition of Deep Packet Inspection System Using the Modernized Hooke ‒ Jeeves Method

Traffic Flows Forecasting Based on Machine Learning

Contact Info

Product

Resources

About