CADIA: Towards Decoupling the Congestion Control for Multipath TCP

Correlating the congestion control (CC) of parallel subflows of multipath TCP (MPTCP) has shown the advantage of making it fair and friendly to legacy TCP. But the correlation also leads to some new drawbacks. In this paper, we first analyze major correlated MPTCP CC algorithms through the perspective of bandwidth competition. Based on the modeling, we verify, discover, and explain three shortages of correlated CC, namely 1) limit fairness semantic; 2) render new attack surfaces; and 3) interplay with network sharing policies. We further find that decoupling the CC of subflows is more promising in solving the above issues. However, directly applying legacy TCP CC to each subflow independently would lose the benefits of correlated CC. This motivates the design of an algorithm that decouples the CC of subflows as much as possible while still making MPTCP fair and friendly. To attain this goal, we translate the goals of correlated CC into an approximation principle under the decoupled semantic. We then propose a self-Constrained And Decoupled Increase Algorithm (CADIA) that achieves the principle by adaptively detecting and constraining non-best subflows. This makes CADIA share the benefits of correlated CC algorithms, while owning no direct correlation among the CC of subflows. Extensive analysis and experiments are conducted to demonstrate the effectiveness of CADIA.