Impact of Packet Sampling on Link Dimensioning

Link dimensioning is used by network operators to properly provision the capacity of their network links. Proposed methods for link dimensioning often require statistics, such as traffic variance, that need to be calculated from packet-level measurements. In practice, due to increasing traffic volume, operators deploy packet sampling techniques aiming to reduce the burden of traffic monitoring, but little is known about how link dimensioning is affected by such measurements. In this paper, we make use of a previously proposed and validated dimensioning formula that requires traffic variance to estimate required link capacity. We assess the impact of three packet sampling techniques on link dimensioning, namely, Bernoulli, n-in-N and sFlow sampling. To account for the additional variance introduced by the sampling algorithms, we propose approaches to better estimate traffic variance from sampled data according to the employed technique. Results show that, depending on sampling rate and link load, packet sampling does not negatively impact on link dimensioning accuracy even at very short timescales such as 10 ms. Moreover, we also show that the loss of inter-arrival time of sampled packets due to the exporting process in sFlow does not harm the estimations, given that an appropriate sampling rate is used. Our study is validated using a large dataset consisting of traffic packet traces captured at several locations around the globe.