Most existing criteria [3], [5], [8] for sizing router buffers rely on explicit formulation of the relationship between buffer size and characteristics of Internet traffic. However, this is a non-trivial, if not impossible, task given that the number of flows, their individual RTTs, and congestion control methods, as well as flow responsiveness, are unknown. In this paper, we undertake a completely different approach that uses controltheoretic buffer-size tuning in response to traffic dynamics. Motivated by the monotonic relationship between buffer size and loss rate and utilization, we design a mechanism called Adaptive Buffer Sizing (ABS), which is composed of two Integral controllers for dynamic buffer adjustment and two gradient-based components for intelligent parameter training. We demonstrate via ns2 simulations that ABS successfully stabilizes the buffer size at its minimum value under given constraints, scales to a wide spectrum of flow populations and link capacities, exhibit...