Throughput and Latency in Finite-Buffer Line Networks

TL;DR

This paper analyzes how finite buffer sizes impact throughput and delay in line networks with erasure links, providing bounds, iterative approximations, and confirming results through simulations.

Contribution

It introduces a Markov chain model for finite-buffer line networks, derives bounds, and proposes iterative schemes for approximating steady-state distributions.

Findings

Throughput capacity remains unchanged without hop-by-hop feedback if network coding is used.

Buffer sizes significantly affect packet delay distribution.

The proposed models accurately predict throughput and delay trends.

Abstract

This work investigates the effect of finite buffer sizes on the throughput capacity and packet delay of line networks with packet erasure links that have perfect feedback. These performance measures are shown to be linked to the stationary distribution of an underlying irreducible Markov chain that models the system exactly. Using simple strategies, bounds on the throughput capacity are derived. The work then presents two iterative schemes to approximate the steady-state distribution of node occupancies by decoupling the chain to smaller queueing blocks. These approximate solutions are used to understand the effect of buffer sizes on throughput capacity and the distribution of packet delay. Using the exact modeling for line networks, it is shown that the throughput capacity is unaltered in the absence of hop-by-hop feedback provided packet-level network coding is allowed. Finally, using simulations, it is confirmed that the proposed framework yields accurate estimates of the throughput capacity and delay distribution and captures the vital trends and tradeoffs in these networks.