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\iteman{io-port 06016276}
\itemau{Bhulai, S.; Hoekstra, G.J.; Bosman, J.W.; van der Mei, R.D.}
\itemti{Dynamic traffic splitting to parallel wireless networks with partial information: a Bayesian approach.}
\itemso{Perform. Eval. 69, No. 1, 41-52 (2012).}
\itemab
Summary: Contemporary wireless networks are based on a wide range of different technologies providing overlapping coverage. This offers users a seamless integration of connectivity by allowing to switch between networks, and opens up a promising area for boosting the performance of wireless networks. Motivated by this, we consider a networking environment in which users are able to select between the available wireless networks to minimize the mean processing times for file downloads in the presence of background traffic. The information available to the user is only the total number of jobs in each network, rather than the per-network numbers of foreground and background jobs. This leads to a complex partial information decision problem which is the focus of this paper.
\itemrv{~}
\itemcc{}
\itemut{traffic splitting; processor sharing; concurrent access; flow-level performance; Bayesian dynamic programming; partial information model}
\itemli{doi:10.1016/j.peva.2011.09.001}
\end