We study the impact of aggregation on the scaling behavior of Internet backbone tra ffic, based on traces collected from OC3 and OC12 links in a tier-1 ISP. We make two striking observations regarding the sub-second small time scaling behaviors of Internet backbone traffic: 1) for a majority of these traces, the Hurst parameters at small time scales (1ms - 100ms) are fairly close to 0.5. Hence the traffic at these time scales are nearly uncorrelated; 2) the scaling behaviors at small time scales are link-dependent, and stay fairly invariant over changing utilization and time. To understand the scaling behavior of network traffic, we develop analytical models and employ them to demonstrate how traffic composition -- aggregation of traffic with different characteristics -- affects the small-time scalings of network traffic. The degree of aggregation and burst correlation structure are two major factors in traffic composition. Our trace-based data analysis confirms this. Furthermore, we discover that traffic composition on a backbone link stays fairly consistent over time and changing utilization, which we believe is the cause for the invariant small-time scalings we observe in the traces.