We investigate the impact of traffic on the performance of large-scale NAT (LSN), since it has been attracting attention as a means of better utilizing the limited number of global IPv4 addresses. We focus on the number of active flows because they drive up the LSN memory requirements in two ways; more flows must be held in LSN memory, and more global IPv4 addresses must be prepared. Through traffic measurement data analysis, we found that more than 1% of hosts generated more than 100 TCP flows or 486 UDP flows at the same time, and on average, there were 1.43-3.99 active TCP flows per host, when the inactive timer used to clear the flow state from a flow table was set to 15 s. When the timer is changed from 15 s to 10 min, the number of active flows increases more than tenfold. We also investigate how to reduce the above impact on LSN in terms of saving memory space and accommodating more users for each global IPv4 address. We show that to save memory space, regulating network anomalies can reduce the number of active TCP flows on an LSN by a maximum of 48.3% and by 29.6% on average. We also discuss the applicability of a batch flow-arrival model for estimating the variation in the number of active flows, when taking into account that the variation is needed to prepare an appropriate memory space. One way to allow each global IPv4 address to accommodate more users is to better utilize destination IP address information when mapping a source IP address from a private address to a global IPv4 address. This can effectively reduce the required number of global IPv4 addresses by 85.9% for TCP traffic and 91.9% for UDP traffic on average.

We develop a method of dimensioning and managing the bandwidth of a link on which TCP flows from access links are aggregated. To do this, we extend the application of the processor-sharing queue model to TCP performance evaluation by using flow statistics. To handle various factors that affect actual TCP behavior, such as round-trip time, window-size, and restrictions other than access-link bandwidth, we extend the model by replacing the access-link bandwidth with the actual file-transfer speed of a flow when the aggregation link is not congested. We only use the number of active flows and the link utilization to estimate the file-transfer speed. Unlike previous studies, the extended model based on the actual transfer speed does not require any assumptions/predeterminations about file-size, packet-size, and round-trip times, etc. Using the extended model, we predict the TCP performance when the link utilization increases. We also show a method of dimensioning the bandwidth needed to maintain TCP performance. We show the effectiveness of our method through simulation analysis.

We propose a method of IP traffic management where the TCP performance at a bottleneck link is estimated from monitored data about the behavior of the number of active flows versus link utilization, which are both easy to measure. This method is based on our findings that (i) TCP performance remains constant as long as the link utilization is below some threshold value, but becomes degraded when it exceeds this value and (ii) the number of active flows increases linearly with link utilization up to the same value, and the increase becomes nonlinear above it. Though this threshold may vary depending on traffic/network conditions, our method requires neither predetermination of a threshold on the basis of assumed traffic conditions nor direct measurement of TCP performance.