Path Diversity over Packet Switched Networks: Performance Analysis and Rate Allocation

TL;DR

This paper analyzes the use of path diversity with FEC over multiple network paths modeled as erasure channels, proving exponential decay of irrecoverable loss and proposing an efficient rate allocation algorithm.

Contribution

It introduces a theoretical framework for optimal rate allocation over multiple paths with FEC, including asymptotic analysis and a practical heuristic algorithm.

Findings

Irrecoverable loss probability decays exponentially with many paths.

Paths with quality below a threshold are assigned zero rate.

Proposed heuristic closely approximates optimal allocation in practice.

Abstract

Path diversity works by setting up multiple parallel connections between the end points using the topological path redundancy of the network. In this paper, \textit{Forward Error Correction} (FEC) is applied across multiple independent paths to enhance the end-to-end reliability. Network paths are modeled as erasure Gilbert-Elliot channels. It is known that over any erasure channel, \textit{Maximum Distance Separable} (MDS) codes achieve the minimum probability of irrecoverable loss among all block codes of the same size. Based on the adopted model for the error behavior, we prove that the probability of irrecoverable loss for MDS codes decays exponentially for an asymptotically large number of paths. Then, optimal rate allocation problem is solved for the asymptotic case where the number of paths is large. Moreover, it is shown that in such asymptotically optimal rate allocation, each path is assigned a positive rate \textit{iff} its quality is above a certain threshold. The quality of a path is defined as the percentage of the time it spends in the bad state. Finally, using dynamic programming, a heuristic suboptimal algorithm with polynomial runtime is proposed for rate allocation over a finite number of paths. This algorithm converges to the asymptotically optimal rate allocation when the number of paths is large. The simulation results show that the proposed algorithm approximates the optimal rate allocation (found by exhaustive search) very closely for practical number of paths, and provides significant performance improvement compared to the alternative schemes of rate allocation.