Self-similar Process - Network Performance

Network Performance

Network performance degrades gradually with increasing self-similarity. The more self-similar the traffic, the longer the queue size. The queue length distribution of self-similar traffic decays more slowly than with Poisson sources. However, long-range dependence implies nothing about its short-term correlations which affect performance in small buffers. Additionally, aggregating streams of self-similar traffic typically intensifies the self-similarity ("burstiness") rather than smoothing it, compounding the problem.

Self-similar traffic exhibits the persistence of clustering which has a negative impact on network performance.

• With Poisson traffic (found in conventional telephony networks), clustering occurs in the short term but smooths out over the long term.
• With self-similar traffic, the bursty behaviour may itself be bursty, which exacerbates the clustering phenomena, and degrades network performance.

Many aspects of network quality of service depend on coping with traffic peaks that might cause network failures, such as

• Cell/packet loss and queue overflow
• Violation of delay bounds e.g. in video
• Worst cases in statistical multiplexing

Poisson processes are well-behaved because they are stateless, and peak loading is not sustained, so queues do not fill. With long-range order, peaks last longer and have greater impact: the equilibrium shifts for a while.