  To reduce computational complexity and delay in randomized network coded
content distribution, and for some other practical reasons, coding is not
performed simultaneously over all content blocks, but over much smaller,
possibly overlapping subsets of these blocks, known as generations. A penalty
of this strategy is throughput reduction. To analyze the throughput loss, we
model coding over generations with random generation scheduling as a coupon
collector's brotherhood problem. This model enables us to derive the expected
number of coded packets needed for successful decoding of the entire content as
well as the probability of decoding failure (the latter only when generations
do not overlap) and further, to quantify the tradeoff between computational
complexity and throughput. Interestingly, with a moderate increase in the
generation size, throughput quickly approaches link capacity. Overlaps between
generations can further improve throughput substantially for relatively small
generation sizes.
