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Measurement-based characterization of IP VPNs
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Source IEEE/ACM Transactions on Networking (TON) archive
Volume 15 ,  Issue 6  (December 2007) table of contents
Pages 1428-1441  
Year of Publication: 2007
ISSN:1063-6692
Authors
Satish Raghunath  Juniper Networks Inc., Sunnyvale, CA
K. K. Ramakrishnan  AT&T Labs-Research, Florham Park, NJ
Shivkumar Kalyanaraman  Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY
Publisher
IEEE Press  Piscataway, NJ, USA
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DOI Bookmark: 10.1109/TNET.2007.896539

ABSTRACT

Virtual Private Networks (VPNs) provide secure and reliable communication between customer sites. With the increase in number and size of VPNs, providers need efficient provisioning techniques that adapt to customer demand by leveraging a good understanding of VPN properties.

In this paper, we analyze two important properties of VPNs that impact provisioning: 1) structure of customer endpoint (CE) interactions and 2) temporal characteristics of CE-CE traffic. We deduce these properties by computing traffic matrices from SNMP measurements. We find that existing traffic matrix estimation techniques are not readily applicable to the VPN scenario due to the scale of the problem and limited measurement information. We begin by formulating a scalable technique that makes the most out of existing measurement information and provides good estimates for common VPN structures. We then use this technique to analyze SNMP measurement information from a large IP VPN service provider.

We find that even with limited measurement information (no per-VPN data for the core) we can estimate traffic matrices for a significant fraction of VPNs, namely, those constituting the "Huband-Spoke" category. In addition, the ability to infer the structure of VPNs holds special significance for provisioning tasks arising from topology changes, link failures and maintenance. We are able to provide a classification of VPNs by structure and identify CEs that act as hubs of communication and hence require prioritized treatment during restoration and provisioning.


REFERENCES

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Collaborative Colleagues:
Satish Raghunath: colleagues
K. K. Ramakrishnan: colleagues
Shivkumar Kalyanaraman: colleagues