Virtual Private Networks provide secure and reliable communication between customer sites. With 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 - (a) structure of customer endpoint (CE) interactions and (b) 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 from a large IP VPN service provider. We find that even with limited me...
Satish Raghunath, K. K. Ramakrishnan, Shivkumar Ka