  Many systems necessitate frequent and consistent updates of a specific
information. Often this information is updated regularly, where an old packet
becomes completely obsolete in the presence of a new packet. In this context,
we consider a system with multiple sources, each equipped with a storage buffer
of size one, communicating to a common destination via d orthogonal channels.
In each slot, the packets arrive at each source with certain probability and
occupy the buffer (by discarding the old packet if any), and each transfer (to
the destination) is successful with certain other probability. Thus in any
slot, there are two (Age of Information) AoI-measures for each source: one
corresponding to the information at the source itself and the other
corresponding to the information of the same source available at the
destination; some sources may not even have the packet to transmit. The aim of
the controller at the destination is to maintain the freshness of information
of all the sources, to the best extent possible -- it aims to design an optimal
scheduling policy that assigns in each slot, a subset of sources with packets
(at maximum d) for transmission. This is achieved using an appropriate Markov
Decision Process (MDP) framework, where the objective function is the sum of
Average AoIs (AAoI) of all the sources. We derive a very simple stationary
policy that is epsilon-optimal -- in any slot, order the sources with packets
in the decreasing order of the differences in AoI at the destination and the
source and choose the top sources for transmission. With moderate number of
sources (less than 30), the AAoI reduces in the range of 30-90%.
