Standard

System architecture for deep packet inspection in high-speed networks. / Khazankin, Grigory R.; Komarov, Sergey; Kovalev, Danila и др.

Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017. Institute of Electrical and Electronics Engineers Inc., 2017. стр. 27-32 8071958.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Khazankin, GR, Komarov, S, Kovalev, D, Barsegyan, A & Likhachev, A 2017, System architecture for deep packet inspection in high-speed networks. в Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017., 8071958, Institute of Electrical and Electronics Engineers Inc., стр. 27-32, 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017, Novosibirsk, Akademgorodok, Российская Федерация, 12.04.2017. https://doi.org/10.1109/SSDSE.2017.8071958

APA

Khazankin, G. R., Komarov, S., Kovalev, D., Barsegyan, A., & Likhachev, A. (2017). System architecture for deep packet inspection in high-speed networks. в Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 (стр. 27-32). [8071958] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSDSE.2017.8071958

Vancouver

Khazankin GR, Komarov S, Kovalev D, Barsegyan A, Likhachev A. System architecture for deep packet inspection in high-speed networks. в Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017. Institute of Electrical and Electronics Engineers Inc. 2017. стр. 27-32. 8071958 doi: 10.1109/SSDSE.2017.8071958

Author

Khazankin, Grigory R. ; Komarov, Sergey ; Kovalev, Danila и др. / System architecture for deep packet inspection in high-speed networks. Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017. Institute of Electrical and Electronics Engineers Inc., 2017. стр. 27-32

BibTeX

@inproceedings{6f8f7a9409eb4b959e937c7e22e7a7ae,
title = "System architecture for deep packet inspection in high-speed networks",
abstract = "To solve the problems associated with large data volume real-time processing, heterogeneous systems using various computing devices are increasingly used. The characteristic of solving this class of problems is related to the fact that there are two directions for improving methods of real-time data analysis: the first is the development of algorithms and approaches to analysis, and the second is the development of hardware and software. This article reviews the main approaches to the architecture of a hardware-software solution for traffic capture and deep packet inspection (DPI) in data transmission networks with a bandwidth of 80 Gbit/s and higher. At the moment there are software and hardware tools that allow designing the architecture of capture system and deep packet inspection: • Using only the central processing unit (CPU); • Using only the graphics processing unit (GPU); • Using the central processing unit and graphics processing unit simultaneously (CPU + GPU). In this paper, we consider these key approaches. Also attention is paid to both hardware and software requirements for the architecture of solutions. Pain points and remedies are described.",
keywords = "CUDA, DMA, DPDK, DPI, GPUDirect, Mellanox, Napatech, NVIDIA, PeerDirect, Zero-copy",
author = "Khazankin, {Grigory R.} and Sergey Komarov and Danila Kovalev and Artur Barsegyan and Alexander Likhachev",
year = "2017",
month = oct,
day = "18",
doi = "10.1109/SSDSE.2017.8071958",
language = "English",
pages = "27--32",
booktitle = "Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 ; Conference date: 12-04-2017 Through 13-04-2017",

}

RIS

TY - GEN

T1 - System architecture for deep packet inspection in high-speed networks

AU - Khazankin, Grigory R.

AU - Komarov, Sergey

AU - Kovalev, Danila

AU - Barsegyan, Artur

AU - Likhachev, Alexander

PY - 2017/10/18

Y1 - 2017/10/18

N2 - To solve the problems associated with large data volume real-time processing, heterogeneous systems using various computing devices are increasingly used. The characteristic of solving this class of problems is related to the fact that there are two directions for improving methods of real-time data analysis: the first is the development of algorithms and approaches to analysis, and the second is the development of hardware and software. This article reviews the main approaches to the architecture of a hardware-software solution for traffic capture and deep packet inspection (DPI) in data transmission networks with a bandwidth of 80 Gbit/s and higher. At the moment there are software and hardware tools that allow designing the architecture of capture system and deep packet inspection: • Using only the central processing unit (CPU); • Using only the graphics processing unit (GPU); • Using the central processing unit and graphics processing unit simultaneously (CPU + GPU). In this paper, we consider these key approaches. Also attention is paid to both hardware and software requirements for the architecture of solutions. Pain points and remedies are described.

AB - To solve the problems associated with large data volume real-time processing, heterogeneous systems using various computing devices are increasingly used. The characteristic of solving this class of problems is related to the fact that there are two directions for improving methods of real-time data analysis: the first is the development of algorithms and approaches to analysis, and the second is the development of hardware and software. This article reviews the main approaches to the architecture of a hardware-software solution for traffic capture and deep packet inspection (DPI) in data transmission networks with a bandwidth of 80 Gbit/s and higher. At the moment there are software and hardware tools that allow designing the architecture of capture system and deep packet inspection: • Using only the central processing unit (CPU); • Using only the graphics processing unit (GPU); • Using the central processing unit and graphics processing unit simultaneously (CPU + GPU). In this paper, we consider these key approaches. Also attention is paid to both hardware and software requirements for the architecture of solutions. Pain points and remedies are described.

KW - CUDA

KW - DMA

KW - DPDK

KW - DPI

KW - GPUDirect

KW - Mellanox

KW - Napatech

KW - NVIDIA

KW - PeerDirect

KW - Zero-copy

UR - http://www.scopus.com/inward/record.url?scp=85040332054&partnerID=8YFLogxK

UR - https://elibrary.ru/item.asp?id=35531488

U2 - 10.1109/SSDSE.2017.8071958

DO - 10.1109/SSDSE.2017.8071958

M3 - Conference contribution

AN - SCOPUS:85040332054

SP - 27

EP - 32

BT - Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017

Y2 - 12 April 2017 through 13 April 2017

ER -

ID: 9642208