  For data streaming applications, existing solutions are not yet able to close
the gap between high data rates and low delay. This work considers the problem
of data streaming under mixed delay constraints over a single communication
channel with delayed feedback. We propose a novel layered adaptive causal
random linear network coding (LAC-RLNC) approach with forward error correction.
LAC-RLNC is a variable-to-variable coding scheme, i.e., variable recovered
information data at the receiver over variable short block length and rate is
proposed. Specifically, for data streaming with base and enhancement layers of
content, we characterize a high dimensional throughput-delay trade-off managed
by the adaptive causal layering coding scheme. The base layer is designed to
satisfy the strict delay constraints, as it contains the data needed to allow
the streaming service. Then, the sender can manage the throughput-delay
trade-off of the second layer by adjusting the retransmission rate a priori and
posterior as the enhancement layer, that contains the remaining data to augment
the streaming service's quality, is with the relax delay constraints. We
numerically show that the layered network coding approach can dramatically
increase performance. We demonstrate that LAC-RLNC compared with the
non-layered approach gains a factor of three in mean and maximum delay for the
base layer, close to the lower bound, and factor two for the enhancement layer.
