{ A Simulation Study Of Token Generation Policies

This paper presents a simulation study of diierent token generation policies for a leaky bucket traac shaper. In particular, the paper addresses the following question: Can the performance of a leaky bucket traac shaper be improved by matching the token generation policy to the characteristics of the input traac? Three diierent token generation policies are considered: Deterministic, Bernoulli, and a Markov Modulated Bernoulli Process (MMBP). Each policy is simulated on three diierent input traf-c models (Deterministic, Bernoulli, and MMBP), using a full factorial experimental design. The simulation results show that, overall, the deterministic token generation policy provides the most consistent performance (lower cell loss and lower cell delay) across a wide range of input traac types. Therefore the deterministic policy is the best token generation policy to use, even if the characteristics of the input traac are known to be other than deterministic.