A performance model for wormhole-switched interconnection networks under self-similar traffic

Many recent studies have convincingly demonstrated that network traffic exhibits a noticeable self-similar nature, which has a considerable impact on queuing performance. However, the networks used in current multicomputers have been primarily designed and analyzed under the assumption of the traditional Poisson arrival process, which is inherently unable to capture traffic self-similarity. Consequently, it is crucial to reexamine the performance properties of multicomputer networks in the context of more realistic traffic models before practical implementations show their potential faults. In an effort toward this end, we propose the first analytical model for wormhole-switched k-ary n-cubes in the presence of self-similar traffic. Simulation experiments demonstrate that the proposed model exhibits a good degree of accuracy for various system sizes and under different operating conditions. The analytical model is then used to investigate the implications of traffic self-similarity on network performance. We reveal that the network suffers considerable performance degradation when subjected to self-similar traffic, stressing the great need for improving network performance to ensure efficient support for this type of traffic.

1 Introduction

A number of recent studies [8], [13], [18], [30] by means of high quality, high time-resolution measurements have convincingly demonstrated that realistic network traffic exhibits self-similar nature and that the traditionally assumed models (e.g., the Poisson process) fail to capture the actual traffic properties. The Poisson arrival process has a characteristic burst length that tends to be smoothed by averaging over a long enough time scale. Rather, measurements of actual traffic indicate that noticeable bursts are present over a wide range of time scales. This fractal-like nature of network traffic can be much better modeled using statistically self-similar processes, which have significantly different theoretical properties from the conventional Poisson process [3], [8], [13], [18], [24], [27], [29], [30]. Since extreme traffic burstiness spanning over a number of time scales gives rise to extended periods of large queue build-ups and also to sustained periods of low activity [21], the phenomenon of traffic self-similarity has a considerable impact on queuing performance and has received significant attention in the networking research community. It has been suggested that many existing theoretical protocols and systems need to be reevaluated under this different type of traffic [3], [13], [24], [27], [30].