On Shortcomings of the ns-2 Random Number Generator

Abstract

The ns-2 is a widely used network simulation tool which implements a fairly old and weak random number generator (RNG). As the RNG component is used by a variety of other components, it can be seen as one of the most important core components of the ns-2. In this paper we explore weaknesses of this RNG and demonstrate its shortcomings in context with a simple simulation example (M/D/1) which produces severely wrong simulation results when this RNG is used in combination with specific seeds. We incorporate the modern Mersenne Twister RNG into the ns-2 and show how the insensitivity of this RNG regarding to the initial seeds leads to significant improvements in the simulation outputs and that this modern RNG has no bad effects with respect to the performance of random number generation.