  We present a heavy traffic analysis of a single-server polling model, with
the special features of retrials and glue periods. The combination of these
features in a polling model typically occurs in certain optical networking
models, and in models where customers have a reservation period just before
their service period. Just before the server arrives at a station there is some
deterministic glue period. Customers (both new arrivals and retrials) arriving
at the station during this glue period will be served during the visit of the
server. Customers arriving in any other period leave immediately and will retry
after an exponentially distributed time. As this model defies a closed-form
expression for the queue length distributions, our main focus is on their
heavy-traffic asymptotics, both at embedded time points (beginnings of glue
periods, visit periods and switch periods) and at arbitrary time points. We
obtain closed-form expressions for the limiting scaled joint queue length
distribution in heavy traffic and use these to accurately approximate the mean
number of customers in the system under different loads.
