Retransmissions serve as the basic
building block that communication protocols use to achieve reliable data
transfer. Until recently, the number of retransmissions was thought to follow a
geometric (light-tailed) distribution. However, recent work shows that when the
distribution of the packet sizes has infinite support, retransmission-based
protocols may result in heavy-tailed delays and possibly zero throughput even
when the aforementioned distribution is light-tailed. In reality, however,
packet sizes are often bounded by the maximum transmission unit (MTU), and thus
the aforementioned result merits a deeper investigation. To that end, in this
paper, we allow the distribution of the packet size L to have finite support.
Under mild conditions, we show that the transmission duration distribution
exhibits a transition from a power-law main body to an exponential tail. The
timescale to observe the power-law main body is roughly equal to the average
transmission duration of the longest packet. The power-law main body, if
significant, may cause the channel throughput to be very close to zero. These
theoretical findings provide an understanding on why some empirical
measurements suggest heavy tails. We use these results to further highlight the
engineering implications of distributions with power-law main bodies and light
tails by analyzing two cases: 1) the throughput of on-off channels with
retransmissions, where we show that even when packet sizes have small means and
bounded support the variability in their sizes can greatly impact system
performance; 2) the distribution of the number of jobs in an M/M/∞ queue with
server failures. Here, we show that retransmissions can cause long-range
dependence and quantify
the impact of the maximum job sizes on the long-range dependence.
dependence and quantify
the impact of the maximum job sizes on the long-range dependence.
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