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Commodity Packet Capture Engines: Tutorial, Cookbook and Applicability

delete2015-01-01
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PRE
AI
V
Víctor Moreno *
J
Javier Ramos
P
Pedro M. Santiago del Río
J
José Luis García‐Dorado
F
Francisco J. Gomez‐Arribas
J
Javier Aracil
DOI:10.1109/COMST.2015.2424887delete
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摘要

摘要

En 中文
Users' demands have dramatically increased due to widespread availability of broadband access and new Internet avenues for accessing, sharing and working with information. In response, operators have upgraded their infrastructures to survive in a market as mature as the current Internet. This has meant that most network processing tasks (e.g., routing, anomaly detection, monitoring) must deal with challenging rates, challenges traditionally accomplished by specialized hardware-e.g., FPGA. However, such approaches lack either flexibility or extensibility-or both. As an alternative, the research community has proposed the utilization of commodity hardware providing flexible and extensible cost-aware solutions, thus entailing lower operational and capital expenditure investments. In this scenario, we explain how the arrival of commodity packet engines has revolutionized the development of traffic processing tasks. Thanks to the optimization of both NIC drivers and standard network stacks and by exploiting concepts such as parallelism and memory affinity, impressive packet capture rates can be achieved in hardware valued at a few thousand dollars. This tutorial explains the foundation of this new paradigm, i.e., the knowledge required to capture packets at multi-Gb/s rates on commodity hardware. Furthermore, we thoroughly explain and empirically compare current proposals, and importantly explain how apply such proposals with a number of code examples. Finally, we review successful use cases of applications developed over these novel engines.
Keyword:
Commodity hardware
packet capture engine
high-performance networking
network traffic monitoring
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期刊

I
IEEE Communications Surveys and Tutorials
IF:
46.7
论文数:
1.5K
被引数:
3.3W

机构

A
Autonomous University of Madrid
学者数:
2.1W
论文数: 1.7W
被引数: 29
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