Latency is becoming a key factor of performance for Internet applications and has triggered a number of changes in its protocols. Our work revisits the impact on latency of address family selection in dual-stack hosts. Through RIPE Atlas measurements, we analyse the address families latency difference and establish two requirements based on our findings for a latency-focused selection mechanism. First, the address family should be chosen per destination. Second, the choice should be able to evolve over time dynamically. We propose and implement a solution formulated as an online learning problem balancing exploration and exploitation. We validate our solution in simulations based on RIPE Atlas measurements, implement and evaluate our prototype in four access networks using Chrome and popular web services. We demonstrate the ability of our solution to converge towards the lowest-latency address family and improve the latency of transport connections used by applications.

翻译：延迟正成为互联网应用性能的关键因素，并已引发其协议的诸多变革。本研究重新审视了双栈主机中地址族选择对延迟的影响。通过RIPE Atlas测量，我们分析了不同地址族间的延迟差异，并基于研究结果建立了面向延迟的选择机制的两项要求：首先，地址族应按目标地址进行选择；其次，该选择应能随时间动态演化。我们提出并实现了一种将问题建模为平衡探索与利用的在线学习解决方案。基于RIPE Atlas测量数据，我们在仿真中验证了该方案，并在四个接入网络中利用Chrome浏览器及主流网络服务对原型系统进行了实施与评估。实验证明，我们的解决方案能够收敛至最低延迟的地址族，并有效改善应用程序传输连接的延迟性能。