Properties of heterogeneous network traffic have been investigated from different aspects, resulting in different understanding. Specifically, one previous work discovers that the variance of network traffic exhibits a linear relationship with respect to the mean. Such a linear relation suggests that the traffic is "Poisson-like", and thus "smooth". On the other hand, prior work has shown that the heterogeneous traffic can be long-range dependent, and is thus bursty. The focus of this work is to investigate these seemingly contradictory issues, and to provide a unified understanding on the burstiness of heterogeneous traffic. In particular, we use a simple statistic, the variance of the traffic, for our investigation. We first study variance-mean relations at a single time scale. We then investigate the behavior of variances at multiple time scales, which determines the temporal correlation structure. Finally, we provide a unified view to include most important understanding of the network traffic.