Delay Bounds in Communication Networks With Heavy-Tailed and Self-Similar Traffic

Traffic with self-similar and heavy-tailed characteristics has been widely reported in communication networks, yet, the state-of-the-art of analytically predicting the delay performance of such networks is lacking. This work addresses heavy-tailed traffic that has a finite first moment, but no second moment, and presents end-to-end delay bounds for such traffic. The derived performance bounds are non-asymptotic in that they do not assume a steady state, large buffer, or many sources regime. The analysis follows a network calculus approach where traffic is characterized by envelope functions and service is described by service curves. The system model is a multi-hop path of fixed-capacity links with heavy-tailed self-similar cross traffic at each node. A key contribution of the paper is a probabilistic sample-path bound for heavy-tailed arrival and service processes, which is based on a scale-free sampling method. The paper explores how delay bounds scale as a function of the length of the path, and compares them with lower bounds. A comparison with simulations illustrates pitfalls when simulating self-similar heavy-tailed traffic, providing further evidence for the need of analytical bounds.