Performance Analysis of Dynamic Equilibria in Joint Path Selection and Congestion Control
Abstract
Path-aware networking, a cornerstone of next-generation architectures like SCION and Multipath QUIC, empowers end-hosts with fine-grained control over traffic forwarding. This capability, however, introduces a critical stability risk: uncoordinated, greedy path selection by a multitude of agents can induce persistent, high-amplitude network oscillations. While this phenomenon is well-known, its quantitative performance impact across key metrics has remained poorly understood. In this paper, we address this gap by developing the first axiomatic framework for analyzing the joint dynamics of path selection and congestion control. Our model enables the formal characterization of the system's dynamic equilibria-the stable, periodic patterns of oscillation-and provides a suite of axioms to rate their performance in terms of efficiency, loss avoidance, convergence, fairness, and responsiveness. Our analysis reveals a fundamental trade-off in protocol design between predictable performance (efficiency, convergence) and user-centric goals (fairness, responsiveness). We prove, however, that no such trade-off exists among efficiency, convergence, and loss avoidance, which can be simultaneously optimized through careful parameter tuning. Furthermore, we find that agent migration can, counter-intuitively, enhance stability by de-synchronizing traffic, a theoretical result validated by our simulations. These findings provide a principled design map for engineering robust, high-performance protocols for the future path-aware Internet.