On the optimization of the token bucket control mechanism

Abstract

During the past years, there has been an increasing interest in the design and development of network traffic controllers capable of ensuring the QoS requirements of a wide range of applications. In this thesis, based on previous work, we use a systems approach to construct a dynamic model for the token bucket mechanism: a traffic controller widely used in various QoS-aware protocol architectures. An enhanced model of multiplexor is also added into the multiple token buckets system model. In this way, the model represents a complete system at the access node of the network. We then develop an optimization algorithm based on a dynamic programming and genetic algorithm approach. Applying two MPEG-1 video traces and two self-similar traffic traces, we conduct an extensive campaign of numerical experiments allowing us to gain insight into the operation of the controller and evaluate the benefits of using a genetic algorithm approach to speed up the computation process based on dynamic programming. Our results show that the optimization is not only capable of getting the best cost, but also balancing the costs corresponding to different aspects. The results also shows that the use of the genetic algorithm proves particular useful in reducing the computation time required to optimize the operation of a system consisting of multiple token-bucket regulated sources.