A programmable architecture for scalable and real-time network traffic measurements

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A programmable architecture for scalable and real-time network traffic measurements

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Symposium On Architecture For Networking And Communications Systems archive
Proceedings of the 4th ACM/IEEE Symposium on Architectures for Networking and Communications Systems table of contents

San Jose, California

SESSION: Measurements and switching table of contents

Pages 109-118

Year of Publication: 2008

ISBN:978-1-60558-346-4

Authors

Faisal Khan	University of California, Davis
Lihua Yuan	University of California, Davis
Chen-Nee Chuah	University of California, Davis
Soheil Ghiasi	University of California, Davis

Sponsors

SIGARCH: ACM Special Interest Group on Computer Architecture
SIGCOMM: ACM Special Interest Group on Data Communication

Publisher

ACM New York, NY, USA

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ABSTRACT

Accurate and real-time traffic measurement is becoming increasingly critical for large variety of applications including accounting, bandwidth provisioning and security analysis. Existing network measurement techniques, however, have major difficulty dealing with large number of flows in today's high-speed networks and offer limited scalability with increasing link speeds. Consequently, the current state of the art solutions have to resort to conservative sampling of the traffic stream and/or accounting for only a few frequent flows that often fail to provide accurate estimates of traffic features.

In this paper, we present a novel hardware-software co-designed solution that is programmable and adaptable to runtime situations offering high-throughputs that can easily match current link-speeds. The key to our design is orthogonalization of memory lookups from traffic measurements through our query-driven measurement scheme. We have prototyped our approach on a Xilinx platform using Microblaze soft-core processors integrated with Virtex-II Pro FPGA fabric. We demonstrate the scalability of our architecture and also compare it with a recent offline (non real-time) sampling-based software alternative. The comparison shows that our architecture performs orders better in terms of speed and throughput even while being used as an offline solution.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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