  Future network services present a significant challenge for network providers
due to high number and high variety of co-existing requirements. Despite many
advancements in network architectures and management schemes, congested network
links continue to constrain the Quality of Service (QoS) for critical
applications like tele-surgery and autonomous driving. A prominent,
complimentary approach consists of congestion control (CC) protocols which
regulate bandwidth at the endpoints before network congestion occurs. However,
existing CC protocols, including recent ones, are primarily designed to handle
small numbers of requirement classes, highlighting the need for a more granular
and flexible congestion control solution.
  In this paper we introduce Hercules, a novel CC protocol designed to handle
heterogeneous requirements. Hercules is based on an online learning approach
and has the capability to support any combination of requirements within an
unbounded and continuous requirements space. We have implemented Hercules as a
QUIC module and demonstrate, through extensive analysis and real-world
experiments, that Hercules can achieve up to 3.5-fold improvement in QoS
compared to state-of-the-art CC protocols.
